Prof. Giuseppe Bonifazi Profile

Prof. Giuseppe Bonifazi

Full Professor at Sapienza Univ di Roma

SPIE Involvement:

Author | Instructor

Publications (63)

Proceedings Article | 27 March 2024 Poster + Paper

Monitoring of macro- and micronutrients in vine leaves by short-wave infrared hyperspectral imaging

Giuseppe Bonifazi, Giuseppe Capobianco, Silvia Serranti, Teodosio D'Apolito

Proceedings Volume 12879, 128790H (2024) https://doi.org/10.1117/12.3009894

KEYWORDS: X-ray fluorescence spectroscopy, Calcium, Chemical elements, Short wave infrared radiation, Silicon, Hyperspectral imaging, Principal component analysis, Zinc, Copper, Potassium, Manganese

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Proceedings Article | 13 June 2023 Poster + Paper

Evaluation of sugar content in hopped wort of artisanal beer by shortwave infrared spectroscopy

Giuseppe Bonifazi, Riccardo Gasbarrone, Silvia Serranti

Proceedings Volume 12545, 125450E (2023) https://doi.org/10.1117/12.2663382

KEYWORDS: Short wave infrared radiation, Smoothing, MATLAB, Spectroscopy, Spectral density, Infrared spectroscopy, Yeast, Near infrared, Cross validation

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Proceedings Article | 22 May 2023 Presentation + Paper

Hyperspectral imaging coupled with data fusion for plastic packaging waste recycling

Giuseppe Bonifazi, Giuseppe Capobianco, Paola Cucuzza, Silvia Serranti

Proceedings Volume 12327, 123270K (2023) https://doi.org/10.1117/12.2645119

KEYWORDS: Plastics, Polymers, Packaging, Data fusion, Short wave infrared radiation, Hyperspectral imaging, Data modeling

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Proceedings Article | 8 March 2023 Poster + Paper

An innovative approach based on hyperspectral imaging for an automatic characterization of post-earthquake building waste

Giuseppe Bonifazi, Giuseppe Capobianco, Silvia Serranti, Oriana Trotta

Proceedings Volume 12428, 1242811 (2023) https://doi.org/10.1117/12.2648405

KEYWORDS: Hyperspectral imaging, Principal component analysis, Calibration, Absorption, Plastics, Data modeling, Short wave infrared radiation, Molecules, Particles, Natural disasters

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Proceedings Article | 8 March 2023 Poster + Paper

On-site spectroscopy as a tool for monitoring phytoremediation by ferns of arsenic contaminated water

Giuseppe Bonifazi, Giuseppe Capobianco, Roberta Palmieri, Silvia Serranti, Maria Luisa Antenozio, Patrizia Brunetti, Maura Cardarelli

Proceedings Volume 12428, 1242810 (2023) https://doi.org/10.1117/12.2648397

KEYWORDS: Near infrared spectroscopy, Arsenic, Contamination, Principal component analysis, Spectroscopy, Calibration, Reflectivity, Data modeling, Water, Matrices, Portability

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Proceedings Article | 14 November 2021 Poster + Presentation + Paper

Hyperspectral imaging approach for the identification of construction and demolition waste from earthquake sites

G. Bonifazi, S. Serranti, O. Trotta

Proceedings Volume 11914, 119141K (2021) https://doi.org/10.1117/12.2616152

KEYWORDS: Cements, Silicon, Hyperspectral imaging, Earthquakes, Calcium, Iron, Chemical analysis, Short wave infrared radiation, Principal component analysis, Aluminum

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Proceedings Article | 12 April 2021 Poster + Presentation + Paper

Hazelnuts classification by hyperspectral imaging coupled with variable selection methods

G. Bonifazi, G. Capobianco, R. Gasbarrone, S. Serranti

Proceedings Volume 11754, 117540Q (2021) https://doi.org/10.1117/12.2588287

KEYWORDS: Hyperspectral imaging, Feature selection, Short wave infrared radiation, Logic, Nondestructive evaluation, Lead, Infrared radiation, Infrared imaging, Agriculture

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Proceedings Article | 5 March 2021 Poster + Presentation + Paper

Detection of olive fruits attacked by olive fruit flies using visible-short wave infrared spectroscopy

Giuseppe Bonifazi, Riccardo Gasbarrone, Silvia Serranti

Proceedings Volume 11693, 1169315 (2021) https://doi.org/10.1117/12.2582712

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Proceedings Article | 13 November 2020 Presentation + Paper

Hyperspectral imaging for VIS-SWIR classification of post-consumer plastic packaging products by polymer and color

S. Serranti, P. Cucuzza, G. Bonifazi

Proceedings Volume 11525, 1152510 (2020) https://doi.org/10.1117/12.2580504

KEYWORDS: Packaging, Polymers, Hyperspectral imaging, Short wave infrared radiation, Sensors, Mathematical modeling, Logic, Contamination

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Proceedings Article | 2 March 2020 Paper

An innovative approach based on hyperspectral imaging (HSI) combined with chemometrics for soil phytoremediation monitoring

Giuseppe Bonifazi, Giuseppe Capobianco, Silvia Serranti, Maria Luisa Antenozio, Patrizia Brunetti, Maura Cardarelli

Proceedings Volume 11287, 112871B (2020) https://doi.org/10.1117/12.2543539

KEYWORDS: Arsenic, Soil contamination, Principal component analysis, Hyperspectral imaging, Calibration, Soil science, Chemometrics, Short wave infrared radiation, Statistical analysis, Chemical analysis

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Proceedings Article | 12 November 2019 Paper

Microplastics characterization by hyperspectral imaging in the SWIR range

Silvia Serranti, Ludovica Fiore, Giuseppe Bonifazi, Ayaka Takeshima, Hisato Takeuchi, Shosaku Kashiwada

Proceedings Volume 11197, 1119710 (2019) https://doi.org/10.1117/12.2542793

KEYWORDS: Hyperspectral imaging, Short wave infrared radiation, Ocean optics, Optical sensors, Environmental sensing, Pollution, Organisms, Coastal modeling, Statistical modeling, Chemometrics

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Proceedings Article | 12 July 2019 Presentation + Paper

Tattoo Wall: study of the stability of an innovative decorative technique through hyperspectral imaging and possible application in the mural painting’s restoration

G. Agresti, G. Bonifazi, G. Capobianco, L. Lanteri, C. Pelosi, S. Serranti, A. Veneri

Proceedings Volume 11058, 110581G (2019) https://doi.org/10.1117/12.2525726

KEYWORDS: Principal component analysis, Hyperspectral imaging, Humidity, Colorimetry, Short wave infrared radiation, Visualization, Spectrophotometry, Printing

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Proceedings Article | 14 May 2019 Paper

Dried red chili peppers pungency assessment by visible and near infrared spectroscopy

Giuseppe Bonifazi, Riccardo Gasbarrone, Silvia Serranti

Proceedings Volume 10986, 109861S (2019) https://doi.org/10.1117/12.2517069

KEYWORDS: Reflectivity, Statistical modeling, Statistical analysis, Calibration, Sensors, Visible radiation, Principal component analysis, Data modeling, Near infrared spectroscopy, Chemometrics

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Proceedings Article | 10 May 2019 Paper

Hyperspectral imaging applied to asbestos containing materials detection: specimen preparation and handling

Silvia Serranti, Giuseppe Bonifazi, Giuseppe Capobianco, Sergio Malinconico, Federica Paglietti

Proceedings Volume 11007, 110070S (2019) https://doi.org/10.1117/12.2517070

KEYWORDS: Statistical analysis, Hyperspectral imaging, Statistical modeling, Calibration, Principal component analysis, Safety, Reflectivity, Chemical analysis, Standards development

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Proceedings Article | 15 May 2018 Paper

Olive fruit ripening evaluation and quality assessment by hyperspectral sensing devices

S. Serranti, G. Bonifazi, R. Gasbarrone

Proceedings Volume 10665, 106650R (2018) https://doi.org/10.1117/12.2297352

KEYWORDS: Short wave infrared radiation, Reflectivity, Principal component analysis, Calibration, Data modeling, Sensors, Hyperspectral imaging, Hyperspectral sensing, MATLAB, Inspection

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Proceedings Article | 15 May 2018 Paper

Kiwifruits ripening assessment by portable hyperspectral devices

S. Serranti, G. Bonifazi, R. Gasbarrone

Proceedings Volume 10665, 106650S (2018) https://doi.org/10.1117/12.2297353

KEYWORDS: Spectroscopy, Reflectivity, Principal component analysis, Calibration, Data modeling, Sensors, Solids, Near infrared, Near infrared spectroscopy, Nondestructive evaluation

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Proceedings Article | 14 May 2018 Presentation + Paper

Near infrared spectroscopy as a tool for in vivo analysis of human muscles

G. Bonifazi, A. Cardillo, A. Currà, R. Gasbarrone, S. Serranti

Proceedings Volume 10662, 106620O (2018) https://doi.org/10.1117/12.2304311

KEYWORDS: Reflectivity, Principal component analysis, Calibration, Near infrared, In vivo imaging, Sensors, Near infrared spectroscopy, Analytical research, Tissues, Chemometrics

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Human skeletal muscles may undergo qualitative and quantitative, physiological and pathological changes during life. Some of these changes may be detected with imaging techniques, others with immunohystochemical and molecular analysis. Both these types of investigation are expensive, time consuming, and not readily available. Therefore, at present, a cheap, reliable, and widely applicable technique for non-invasive in vivo analysis of human muscles is lacking. Here we propose optical spectroscopy as a tool that can be added to clinical investigation without significant cost and time penalties. Recent advances in materials and fabrication techniques provided portable, performant, sensing optical spectrometers readily operated by user-friendly cabled or wireless systems. Such systems allow rapid, non-invasive and not destructive quantitative analysis of human tissues. In this investigation, we tested whether infrared spectroscopy techniques, currently utilized in many areas as primary/secondary raw materials sector, cultural heritage, agricultural/food industry, environmental remote and proximal sensing, pharmaceutical industry, etc., could be applied in living humans to categorize muscles. We acquired muscles reflectance spectra in the Vis-SWIR regions (350-2500 nm), utilizing an ASD FieldSpec 4™ Standard-Res Spectroradiometer with a spectral sampling capability of 1.4 nm at 350- 1000 nm and 1.1 nm at 1001-2500 nm. Spectra were collected from the upper limb muscles (i.e. biceps, a forearm flexor, and triceps, a forearm extensor) placed in fixed limb postures (elbow angle approximately 90°) of 22 healthy subjects (age 25-89 years, 11 females). Spectra off-line analysis included preliminary pre-processing for signal scattering reduction, Principal Component Analysis (PCA) aimed to spectral grouping and Partial Least-Squares Discriminant Analysis (PLS-DA) for implementing discrimination/prediction models. Spectral data were correlated with anthropometric variables. Optical spectroscopy proved effective for studying human muscles in vivo. Vis-SWIR spectra acquired from the arm detect muscles from other tissues, and distinguished flexors from extensors.

Proceedings Article | 21 February 2018 Paper

Near infrared spectroscopy of human muscles

R. Gasbarrone, A. Currà, A. Cardillo, G. Bonifazi, S. Serranti

Proceedings Volume 10489, 1048914 (2018) https://doi.org/10.1117/12.2287814

KEYWORDS: Principal component analysis, Reflectivity, Sensors, Calibration, Near infrared spectroscopy, Near infrared, Data modeling, Chemometrics, Analytical research, Tissues

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Proceedings Article | 1 May 2017 Paper

Classification of Peronospora infected grapevine leaves with the use of hyperspectral imaging analysis

S. Serranti, G. Bonifazi, V. Luciani, L. D'Aniello

Proceedings Volume 10217, 102170N (2017) https://doi.org/10.1117/12.2255052

KEYWORDS: Near infrared, Vegetation, Principal component analysis, Cameras, Reflectivity, Tissues, Visible radiation, Image classification, Hyperspectral imaging, Remote sensing, Chemometrics, Multispectral imaging, Optical sensors, Image sensors

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Proceedings Article | 1 May 2017 Paper

Non-destructive quality control of kiwi fruits by hyperspectral imaging

S. Serranti, G. Bonifazi, V. Luciani

Proceedings Volume 10217, 102170O (2017) https://doi.org/10.1117/12.2255055

KEYWORDS: Hyperspectral imaging, Nondestructive evaluation, Principal component analysis, Near infrared, RGB color model, Cameras, Neodymium, Liquids, Solids, Reflectivity

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SPIE Journal Paper | 15 October 2016

Hyperspectral imaging as a technique for investigating the effect of consolidating materials on wood

Giuseppe Bonifazi, Silvia Serranti, Giuseppe Capobianco, Giorgia Agresti, Luca Calienno, Rodolfo Picchio, Angela Lo Monaco, Ulderico Santamaria, Claudia Pelosi

JEI, Vol. 26, Issue 01, 011003, (October 2016) https://doi.org/10.1117/12.10.1117/1.JEI.26.1.011003

KEYWORDS: Hyperspectral imaging, Principal component analysis, Statistical modeling, Data modeling, Absorption, Epoxies, Statistical analysis, Reflectivity, Short wave infrared radiation, Data processing

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Proceedings Article | 26 May 2016 Paper

Characterization of a new fertilizer during field trials by hyperspectral imaging

Giuseppe Bonifazi, Silvia Serranti, Agata Trella, Carlos Garcia Izquierdo

Proceedings Volume 9864, 98640J (2016) https://doi.org/10.1117/12.2223006

KEYWORDS: Reflectivity, Hyperspectral imaging, Principal component analysis, Agriculture, Near infrared, Chemical analysis, Calibration, Carbon, Soil science, Nitrogen

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Proceedings Article | 9 May 2016 Paper

Study of consolidating materials applied on wood by hyperspectral imaging

G. Bonifazi, S. Serranti, G. Capobianco, G. Agresti, L. Calienno, R. Picchio, A. Lo Monaco, U. Santamaria, C. Pelosi

Proceedings Volume 9862, 98620I (2016) https://doi.org/10.1117/12.2223013

KEYWORDS: Hyperspectral imaging, Chemometrics, Data modeling, Epoxies, Short wave infrared radiation, Data processing, Thermal modeling, Statistical modeling, Modeling, Heart, Principal component analysis, Polonium, Statistical analysis, Absorption

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Proceedings Article | 29 April 2016 Paper

Hyperspectral imaging and its applications

S. Serranti, G. Bonifazi

Proceedings Volume 9899, 98990P (2016) https://doi.org/10.1117/12.2234976

KEYWORDS: Hyperspectral imaging, Material characterization, Process control, Spectroscopy, Inspection, Algorithm development, Logic, Optical sensing, Digital cameras, Imaging spectroscopy, Statistical analysis, Near infrared, Chemical analysis, Principal component analysis, Reflectivity, Digital imaging

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Hyperspectral imaging (HSI) is an emerging technique that combines the imaging properties of a digital camera with the spectroscopic properties of a spectrometer able to detect the spectral attributes of each pixel in an image. For these characteristics, HSI allows to qualitatively and quantitatively evaluate the effects of the interactions of light with organic and/or inorganic materials. The results of this interaction are usually displayed as a spectral signature characterized by a sequence of energy values, in a pre-defined wavelength interval, for each of the investigated/collected wavelength. Following this approach, it is thus possible to collect, in a fast and reliable way, spectral information that are strictly linked to chemical-physical characteristics of the investigated materials and/or products. Considering that in an hyperspectral image the spectrum of each pixel can be analyzed, HSI can be considered as one of the best nondestructive technology allowing to perform the most accurate and detailed information extraction. HSI can be applied in different wavelength fields, the most common are the visible (VIS: 400-700 nm), the near infrared (NIR: 1000-1700 nm) and the short wave infrared (SWIR: 1000-2500 nm). It can be applied for inspections from micro- to macro-scale, up to remote sensing. HSI produces a large amount of information due to the great number of continuous collected spectral bands. Such an approach, when successful, is quite challenging being usually reliable, robust and characterized by lower costs, if compared with those usually associated to commonly applied analytical off-line and/or on-line analytical approaches. More and more applications have been thus developed and tested, in these last years, especially in food inspection, with a large range of investigated products, such as fruits and vegetables, meat, fish, eggs and cereals, but also in medicine and pharmaceutical sector, in cultural heritage, in material characterization and in waste recycling. Examples of some application, based on HSI, originally developed by the authors, are presented, critically analyzed and discussed, with reference to the different hardware configuration and logics utilized to perform the analysis, according to the characterization, inspection and quality control actions to apply.

SPIE Journal Paper | 23 July 2015 Open Access

Hyperspectral imaging applied to demolition waste recycling: innovative approach for product quality control

Silvia Serranti, Roberta Palmieri, Giuseppe Bonifazi

JEI, Vol. 24, Issue 04, 043003, (July 2015) https://doi.org/10.1117/12.10.1117/1.JEI.24.4.043003

KEYWORDS: Hyperspectral imaging, Particles, Statistical modeling, Data modeling, Principal component analysis, Foam, Near infrared, Statistical analysis, Image classification, Sensors

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Proceedings Article | 13 May 2015 Paper

Production of an innovative fertilizer from organic waste: process monitoring by hyperspectral imaging

Silvia Serranti, Giuseppe Bonifazi, Andrea Fabbri, Alice Dall'Ara, Carlos Garcia Izquierdo

Proceedings Volume 9488, 948812 (2015) https://doi.org/10.1117/12.2176541

KEYWORDS: Carbon, Near infrared, Agriculture, Calibration, Hyperspectral imaging, Nitrogen, Minerals, Data modeling, Statistical analysis, Statistical modeling

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Proceedings Article | 13 May 2015 Paper

Quality control in the recycling stream of PVC cable waste by hyperspectral imaging analysis

Valentina Luciani, Silvia Serranti, Giuseppe Bonifazi, Peter Rem

Proceedings Volume 9486, 948610 (2015) https://doi.org/10.1117/12.2176195

KEYWORDS: Copper, Particles, Hyperspectral imaging, Near infrared, Principal component analysis, Magnetism, Control systems, Polymers, Metals, Calibration

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Proceedings Article | 13 March 2015 Paper

Short wave infrared hyperspectral imaging for recovered post-consumer single and mixed polymers characterization

Giuseppe Bonifazi, Roberta Palmieri, Silvia Serranti

Proceedings Volume 9403, 94030R (2015) https://doi.org/10.1117/12.2081362

KEYWORDS: Polymers, Polymethylmethacrylate, Hyperspectral imaging, Data modeling, Short wave infrared radiation, Cell phones, Principal component analysis, Packaging, Digital imaging, Picosecond phenomena

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Proceedings Article | 27 February 2015 Paper

Innovative hyperspectral imaging (HSI) based techniques applied to end-of-life concrete drill core characterization for optimal dismantling and materials recovery

Giuseppe Bonifazi, Nicoletta Picone, Silvia Serranti

Proceedings Volume 9405, 94050X (2015) https://doi.org/10.1117/12.2081174

KEYWORDS: Cements, Particles, Statistical modeling, Data modeling, Statistical analysis, Hyperspectral imaging, Short wave infrared radiation, Absorption, Principal component analysis, Infrared radiation

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SPIE Journal Paper | 5 December 2014 Open Access

Taking advantage of hyperspectral imaging classification of urinary stones against conventional infrared spectroscopy

Francisco Blanco, Felipe Lumbreras, Joan Serrat, Roswitha Siener, Silvia Serranti, Giuseppe Bonifazi, Montserrat López-Mesas, Manuel Valiente

JBO, Vol. 19, Issue 12, 126004, (December 2014) https://doi.org/10.1117/12.10.1117/1.JBO.19.12.126004

KEYWORDS: Infrared spectroscopy, Statistical analysis, Hyperspectral imaging, Statistical modeling, Infrared imaging, Calcium, Chemical analysis, Near infrared, Spectroscopy, Microscopy

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Proceedings Article | 28 May 2014 Paper

A HyperSpectral Imaging (HSI) approach for bio-digestate real time monitoring

Giuseppe Bonifazi, Andrea Fabbri, Silvia Serranti

Proceedings Volume 9108, 91080V (2014) https://doi.org/10.1117/12.2049310

KEYWORDS: Agriculture, Calibration, Soil contamination, Near infrared, Hyperspectral imaging, Statistical modeling, Chemical analysis, Nitrogen, Statistical analysis, Data modeling

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One of the key issues in developing Good Agricultural Practices (GAP) is represented by the optimal utilisation of fertilisers and herbicidal to reduce the impact of Nitrates in soils and the environment. In traditional agriculture practises, these substances were provided to the soils through the use of chemical products (inorganic/organic fertilizers, soil improvers/conditioners, etc.), usually associated to several major environmental problems, such as: water pollution and contamination, fertilizer dependency, soil acidification, trace mineral depletion, over-fertilization, high energy consumption, contribution to climate change, impacts on mycorrhizas, lack of long-term sustainability, etc. For this reason, the agricultural market is more and more interested in the utilisation of organic fertilisers and soil improvers. Among organic fertilizers, there is an emerging interest for the digestate, a sub-product resulting from anaerobic digestion (AD) processes. Several studies confirm the high properties of digestate if used as organic fertilizer and soil improver/conditioner. Digestate, in fact, is somehow similar to compost: AD converts a major part of organic nitrogen to ammonia, which is then directly available to plants as nitrogen. In this paper, new analytical tools, based on HyperSpectral Imaging (HSI) sensing devices, and related detection architectures, is presented and discussed in order to define and apply simple to use, reliable, robust and low cost strategies finalised to define and implement innovative smart detection engines for digestate characterization and monitoring. This approach is finalized to utilize this “waste product” as a valuable organic fertilizer and soil conditioner, in a reduced impact and an “ad hoc” soil fertilisation perspective. Furthermore, the possibility to contemporary utilize the HSI approach to realize a real time physicalchemical characterisation of agricultural soils (i.e. nitrogen, phosphorus, etc., detection) could allow to set up “real time” selective fertilization strategies in order to obtain a safer culture production.

Proceedings Article | 22 May 2014 Paper

Pigment identification in pictorial layers by HyperSpectral Imaging

Giuseppe Capobianco, Giuseppe Bonifazi, Fernanda Prestileo, Silvia Serranti

Proceedings Volume 9106, 91060B (2014) https://doi.org/10.1117/12.2049941

KEYWORDS: Absorption, Minerals, Cobalt, Reflectivity, Principal component analysis, RGB color model, Carbonates, Hyperspectral imaging, Short wave infrared radiation, Calibration

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Proceedings Article | 22 May 2014 Paper

Automatic detection and classification of EOL-concrete and resulting recovered products by hyperspectral imaging

Roberta Palmieri, Giuseppe Bonifazi, Silvia Serranti

Proceedings Volume 9106, 91060D (2014) https://doi.org/10.1117/12.2049399

KEYWORDS: Principal component analysis, Foam, Hyperspectral imaging, Particles, Near infrared, Data modeling, Image classification, Cameras, Analytical research, Statistical analysis

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Proceedings Article | 7 March 2014 Paper

Quality control by HyperSpectral Imaging (HSI) in solid waste recycling: logics, algorithms and procedures

Giuseppe Bonifazi, Silvia Serranti

Proceedings Volume 9024, 90240T (2014) https://doi.org/10.1117/12.2038374

KEYWORDS: Polymers, Logic, Solids, Hyperspectral imaging, Statistical analysis, Principal component analysis, Algorithm development, Near infrared, Reflectivity, Cell phones

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In secondary raw materials and recycling sectors, the products quality represents, more and more, the key issue to pursuit in order to be competitive in a more and more demanding market, where quality standards and products certification play a preheminent role. These goals assume particular importance when recycling actions are applied. Recovered products, resulting from waste materials, and/or dismissed products processing, are, in fact, always seen with a certain suspect. An adequate response of the industry to the market can only be given through the utilization of equipment and procedures ensuring pure, high-quality production, and efficient work and cost. All these goals can be reached adopting not only more efficient equipment and layouts, but also introducing new processing logics able to realize a full control of the handled material flow streams fulfilling, at the same time, i) an easy management of the procedures, ii) an efficient use of the energy, iii) the definition and set up of reliable and robust procedures, iv) the possibility to implement network connectivity capabilities finalized to a remote monitoring and control of the processes and v) a full data storage, analysis and retrieving. Furthermore the ongoing legislation and regulation require the implementation of recycling infrastructure characterised by high resources efficiency and low environmental impacts, both aspects being strongly linked to the waste materials and/or dismissed products original characteristics. For these reasons an optimal recycling infrastructure design primarily requires a full knowledge of the characteristics of the input waste. What previously outlined requires the introduction of a new important concept to apply in solid waste recycling, the recycling-oriented characterization, that is the set of actions addressed to strategically determine selected attributes, in order to get goaloriented data on waste for the development, implementation or improvement of recycling strategies. The problems arising when suitable HyperSpectral Imaging (HSI) based procedures have to be developed and implemented to solid waste products characterization, in order to define time efficient compression and interpretation techniques, are thus analyzed and discussed in the following. Particular attention was also addressed to define an integrated hardware and software (HW and SW) platform able to perform a non-intrusive, non-contact and real-time analysis and embedding a core of analytical logics and procedures to utilize both at laboratory and industrial scale. Several case studies, referred to waste plastics products, are presented and discussed.

Proceedings Article | 4 March 2014 Paper

Hyperspectral imaging applied to end-of-life concrete recycling

Silvia Serranti, Giuseppe Bonifazi

Proceedings Volume 9022, 90220V (2014) https://doi.org/10.1117/12.2039242

KEYWORDS: Glasses, Hyperspectral imaging, Principal component analysis, Near infrared, Statistical analysis, Calibration, Reflectivity, Image classification, Image sensors, Sensors

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Proceedings Article | 25 February 2014 Paper

2D-fractal based algorithms for nanoparticles characterization

Giuseppe Bonifazi, Silvia Serranti

Proceedings Volume 9019, 90190K (2014) https://doi.org/10.1117/12.2038392

KEYWORDS: Fractal analysis, Particles, Image processing, Statistical analysis, Nanoparticles, Darmstadtium, Selenium, Image segmentation, Copper, Image analysis

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Proceedings Article | 3 May 2013 Paper

Quality control in the recycling stream of PVC from window frames by hyperspectral imaging

Valentina Luciani, Silvia Serranti, Giuseppe Bonifazi, Francesco Di Maio, Peter Rem

Proceedings Volume 8774, 87741N (2013) https://doi.org/10.1117/12.2014755

KEYWORDS: Particles, Principal component analysis, Hyperspectral imaging, Near infrared, Reflectivity, Polymers, Statistical analysis, Data modeling, Algorithm development, Glasses

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Proceedings Article | 3 May 2013 Paper

A new hyperspectral imaging based device for quality control in plastic recycling

G. Bonifazi, M. D'Agostini, A. Dall'Ava, S. Serranti, F. Turioni

Proceedings Volume 8774, 87741M (2013) https://doi.org/10.1117/12.2014909

KEYWORDS: Sensors, Hyperspectral imaging, Control systems, Data acquisition, Data modeling, Spectroscopy, Image processing, Image classification, Algorithm development, Mathematical modeling

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Proceedings Article | 19 February 2013 Paper

Ore minerals textural characterization by hyperspectral imaging

Giuseppe Bonifazi, Nicoletta Picone, Silvia Serranti

Proceedings Volume 8655, 865510 (2013) https://doi.org/10.1117/12.2003054

KEYWORDS: Minerals, Principal component analysis, Lead, Hyperspectral imaging, Spectroscopy, Reflectivity, Near infrared, Statistical analysis, Calibration, Remote sensing

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The utilization of hyperspectral detection devices, for natural resources mapping/exploitation through remote sensing techniques, dates back to the early 1970s. From the first devices utilizing a one-dimensional profile spectrometer, HyperSpectral Imaging (HSI) devices have been developed. Thus, from specific-customized devices, originally developed by Governmental Agencies (e.g. NASA, specialized research labs, etc.), a lot of HSI based equipment are today available at commercial level. Parallel to this huge increase of hyperspectral systems development/manufacturing, addressed to airborne application, a strong increase also occurred in developing HSI based devices for “ground” utilization that is sensing units able to play inside a laboratory, a processing plant and/or in an open field. Thanks to this diffusion more and more applications have been developed and tested in this last years also in the materials sectors. Such an approach, when successful, is quite challenging being usually reliable, robust and characterised by lower costs if compared with those usually associated to commonly applied analytical off- and/or on-line analytical approaches. In this paper such an approach is presented with reference to ore minerals characterization. According to the different phases and stages of ore minerals and products characterization, and starting from the analyses of the detected hyperspectral firms, it is possible to derive useful information about mineral flow stream properties and their physical-chemical attributes. This last aspect can be utilized to define innovative process mineralogy strategies and to implement on-line procedures at processing level. The present study discusses the effects related to the adoption of different hardware configurations, the utilization of different logics to perform the analysis and the selection of different algorithms according to the different characterization, inspection and quality control actions to apply.

SPIE Journal Paper | 25 July 2012 Open Access

Hyperspectral imaging based method for fast characterization of kidney stone types

Francisco Blanco, Montserrat Lopez-Mesas, Manuel Valiente, Silvia Serranti, Giuseppe Bonifazi, Josef Havel

JBO, Vol. 17, Issue 7, 076027, (July 2012) https://doi.org/10.1117/12.10.1117/1.JBO.17.7.076027

KEYWORDS: Renal calculi, Statistical analysis, Principal component analysis, Hyperspectral imaging, Near infrared, Reflectivity, Data modeling, Scanning electron microscopy, Crystals, Imaging systems

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SPIE Journal Paper | 14 June 2012

Hyperspectral imaging techniques applied to the monitoring of wine waste anaerobic digestion process

Silvia Serranti, Andrea Fabbri, Giuseppe Bonifazi

OE, Vol. 51, Issue 11, 111708, (June 2012) https://doi.org/10.1117/12.10.1117/1.OE.51.11.111708

KEYWORDS: Biogases, Magnesium, Hyperspectral imaging, Calibration, Chemical analysis, Near infrared, Solids, Industrial chemicals, Optical engineering, Data modeling

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Proceedings Article | 9 May 2012 Paper

Hyperspectral-imaging-based techniques applied to wheat kernels characterization

Silvia Serranti, Daniela Cesare, Giuseppe Bonifazi

Proceedings Volume 8369, 83690T (2012) https://doi.org/10.1117/12.918559

KEYWORDS: Vitreous, Principal component analysis, Hyperspectral imaging, Near infrared, Reflectivity, Statistical modeling, Image classification, Digital imaging, Calibration, Statistical analysis

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Proceedings Article | 9 May 2012 Paper

Application of NIR hyperspectral imaging for post-consumer polyolefins recycling

Silvia Serranti, Aldo Gargiulo, Giuseppe Bonifazi

Proceedings Volume 8366, 83660G (2012) https://doi.org/10.1117/12.918556

KEYWORDS: Hyperspectral imaging, Principal component analysis, Near infrared, Particles, Positron emission tomography, Polymers, Solids, Imaging spectroscopy, Multispectral imaging, Logic

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Proceedings Article | 7 May 2012 Paper

Dried fruits quality assessment by hyperspectral imaging

Silvia Serranti, Aldo Gargiulo, Giuseppe Bonifazi

Proceedings Volume 8369, 83690U (2012) https://doi.org/10.1117/12.918561

KEYWORDS: Principal component analysis, Hyperspectral imaging, Near infrared, Reflectivity, Imaging spectroscopy, Logic, Spectroscopy, Imaging systems, Signal processing, RGB color model

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Proceedings Article | 30 April 2008 Paper

Compost quality control by hyperspectral imaging

Giuseppe Bonifazi, Silvia Serranti, Laura D'Aniello

Proceedings Volume 7003, 700321 (2008) https://doi.org/10.1117/12.781639

KEYWORDS: Reflectivity, Glasses, Hyperspectral imaging, Particles, Solids, Imaging systems, Principal component analysis, Metals, Visible radiation, Statistical analysis

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Proceedings Article | 26 April 2008 Paper

Hyperspectral imaging applied to complex particulate solids systems

Giuseppe Bonifazi, Silvia Serranti

Proceedings Volume 7003, 70030F (2008) https://doi.org/10.1117/12.781641

KEYWORDS: Hyperspectral imaging, Imaging systems, Reflectivity, Principal component analysis, Imaging spectroscopy, Image analysis, Solids, Statistical analysis, Near infrared, Manufacturing

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Proceedings Article | 12 October 2007 Paper

Application of multispectral remote sensing techniques for dismissed mine sites monitoring and rehabilitation

Giuseppe Bonifazi, Silvia Serranti

Proceedings Volume 6761, 676104 (2007) https://doi.org/10.1117/12.735810

KEYWORDS: Mining, Satellites, Landsat, Image resolution, Earth observing sensors, Land mines, Satellite imaging, Environmental sensing, Geographic information systems, Visualization

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Mining activities, expecially those operated in open air (open pit), present a deep impact on the sourrondings. Such an impact, and the related problems, are directly related to the correct operation of the activities, and usually strongly interact with the environment. Impact can be mainly related to the following issues: high volumes of handled material, ii) generation of dust, noise and vibrations, water pollution, visual impact and, finally, mining area recovery at the end of exploitation activities. All these aspects can be considered very important, and must be properly evaluated and monitored. Environmental impact control is usually carried out during and after the end of the mining activities, adopting methods related to the detection, collection, analysis of specific environmental indicators and with their further comparison with reference thresholding values stated by official regulations. Aim of the study was to investigate, and critically evaluate, the problems related to development of an integrated set of procedures based on the collection and the analysis of remote sensed data in order to evaluate the effect of rehabilitation of land contaminated by extractive industry activities. Starting from the results of these analyses, a monitoring and registration of the environmental impact of such operations was performed by the application and the integration of modern information technologies, as the previous mentioned Earth Observation (EO), with Geographic Information Systems (GIS). The study was developed with reference to different dismissed mine sites in India, Thailand and China. The results of the study have been utilized as input for the construction of a knowledge based decision support system finalized to help in the identification of the appropriate rehabilitation technologies for all those dismissed area previously interested by extractive industry activities. The work was financially supported within the framework of the Project ASIA IT&C - CN/ASIA IT&C/006 (89870) Extract-It "Application of Information Technologies for the Sustainable Management of Extractive Industry Activities" of the European Union.

Proceedings Article | 8 October 2007 Paper

Hyperspectral imaging based procedures applied to bottom ash characterization

Giuseppe Bonifazi, Silvia Serranti

Proceedings Volume 6755, 67550B (2007) https://doi.org/10.1117/12.735803

KEYWORDS: Hyperspectral imaging, Reflectivity, Glasses, Combustion, Solids, Statistical analysis, Image processing, Particles, Ceramics, Metals

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Proceedings Article | 21 February 2007 Paper

Thermal-imaging-based procedures for special concretes characterization

Giuseppe Bonifazi, Mauro Animali, Luca Damiani

Proceedings Volume 6501, 65010F (2007) https://doi.org/10.1117/12.694874

KEYWORDS: Cements, Thermography, Particles, Image segmentation, Adsorption, Carbonates, Statistical analysis, Infrared radiation, Silica, Iron

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Proceedings Article | 20 February 2007 Paper

Imaging-based logics for ornamental stone quality chart definition

Giuseppe Bonifazi, Aldo Gargiulo, Silvia Serranti, Costantino Raspi

Proceedings Volume 6503, 65030P (2007) https://doi.org/10.1117/12.694879

KEYWORDS: Polishing, Surface finishing, Polishing equipment, Abrasives, Statistical analysis, RGB color model, Logic, Manufacturing, Software development, Image processing

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Proceedings Article | 23 October 2006 Paper

Hyperspectral imaging based techniques applied to polluted clay characterization

Giuseppe Bonifazi, Silvia Serranti

Proceedings Volume 6381, 638101 (2006) https://doi.org/10.1117/12.684660

KEYWORDS: Soil contamination, Soil science, Hyperspectral imaging, Statistical analysis, Light sources and illumination, Reflectivity, Solids, Cameras, Signal processing, Spectrophotometry

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Proceedings Article | 17 October 2006 Paper

Hyperspectral imaging based techniques in fluff characterization

Giuseppe Bonifazi, Silvia Serranti

Proceedings Volume 6377, 63770O (2006) https://doi.org/10.1117/12.684661

KEYWORDS: Metals, Hyperspectral imaging, Reflectivity, Particles, Glasses, Imaging systems, Near infrared, Imaging spectroscopy, Algorithm development, Foam

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Proceedings Article | 9 November 2005 Paper

Hyperspectral imaging based techniques in contaminated soils characterization

Giuseppe Bonifazi, Luigi Piga, Silvia Serranti, Paolo Menesatti

Proceedings Volume 5996, 59960O (2005) https://doi.org/10.1117/12.629427

KEYWORDS: Soil contamination, Mercury, Soil science, Particles, Reflectivity, Statistical analysis, Adsorption, Hyperspectral imaging, Agriculture, Light sources and illumination

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Proceedings Article | 9 November 2005 Paper

Hyperspectral imaging based techniques in ornamental stone characterization

Giuseppe Bonifazi, Silvia Serranti, Paolo Menesatti

Proceedings Volume 5996, 59960N (2005) https://doi.org/10.1117/12.629426

KEYWORDS: Surface finishing, Polishing, Manufacturing, Hyperspectral imaging, Reflectivity, Light sources and illumination, Signal processing, Control systems, Imaging systems

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Proceedings Article | 19 November 2004 Paper

Multi and hyperspectral digital-imaging-based techniques for agricultural soil characterization

Giuseppe Bonifazi, Paolo Menesatti, Mario Millozza

Proceedings Volume 5587, (2004) https://doi.org/10.1117/12.569518

KEYWORDS: Soil science, Agriculture, Data modeling, Near infrared, Statistical analysis, Spectrophotometry, Reflectivity, Signal processing, Calibration, Chemical analysis

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Proceedings Article | 25 October 2004 Paper

Classical imaging and digital imaging spectrophotometric techniques in cullets (glass fragments) sorting

Giuseppe Bonifazi

Proceedings Volume 5608, (2004) https://doi.org/10.1117/12.569515

KEYWORDS: Glasses, Ceramics, Digital imaging, Laser applications, Light sources and illumination, Sensors, Spectrophotometry, Logic, Light, RGB color model

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Cullets optical sorting represents one of the oldest selection procedure applied to the field of solid waste recycling. From the original sorting strategies, mainly addressed to separate non-transparent elements (ceramics, stones, metal particles, etc.) from transparent ones (glass fragments), the attention was addressed to define procedures and actions able to separate the cullets according to their color characteristics and, more recently, to recognize transparent ceramic glass from glass. Cullets sorting is currently realized adopting, as detecting architecture, laser beam technology based devices. The sorting logic is mainly analogical. An “on-off” logic is applied. Detection is, in fact, based on the evaluation of the “characteristics” of the energy (transparent or non-transparent fragment) and the spectra (fragment color attributes) received by a detector after that cullets were crossed by a suitable laser beam light. Such an approach presents some limits related with the technology utilized and the material characteristics. The technological limits are linked to the physical dimension and the mechanical arrangement of the optics carrying out and in the signals, and with the pneumatic architectures enabling the modification of cullets trajectory to realize sorting, according to their characteristics (color and transmittance). Furthermore such devices are practically “blind” in the recognition of ceramic glasses, whose presence in the final selected material to melt, damage the full recycled glass fusion compromising the quality of the final product. In the following it will be described the work developed, and the results achieved, in order to design a full integrated classical digital imaging and spectrophotometric based approach addressed to develop suitable sorting strategies able to perform, at industrial recycling scale, the distinction of cullets both in terms of color and material typologies, that is “real glass” from “ceramic glass” fragments.

Proceedings Article | 28 May 2004 Paper

Imaging-based dust sensors: equipment and methods

Giuseppe Bonifazi, Sonia Greco

Proceedings Volume 5298, (2004) https://doi.org/10.1117/12.524793

KEYWORDS: Particles, Statistical analysis, Image processing, Logic, Fractal analysis, Imaging systems, Image segmentation, Particle systems, Control systems, Image analysis

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Dust detection and control in real time, represent one of the most challenging problem in all those environments where fine and ultrafine airborne particulate solids products are present. The presence of such products can be linked to several factors, often directly related and influenced by the working-production actions performed. Independently from the causes generating dust, airborne contaminants are an occupational problem of increasing interest as they are related to a wide number of diseases. In particular, airborne dusts are well known to be associated with several classical occupational lung diseases, such as the pneumoconiosis, especially at high levels of exposure. Nowadays there is also an increasing interest in other dust related diseases, from the most serious as cancer and asthma, to those related with allergies or irritation and other illnesses, also occurring at lower levels of exposure. Among the different critical factors influencing health risk for airborne dust exposure, mainly four have to be considered, that is: i) nature of the dust resulting from working in terms of presence of specific poisoning material, i.e. free silica, and morphological and morphometrical attributes of particulates constituting airborne dust; ii) size of the particles, iii) duration of exposure time and, finally, iv) airborne dust concentration in the breathing zone where the worker performs his activity. A correct dust detection is not easy, especially if some of the previous mentioned factors, have to be detected and quantified in real time in order to define specific “on-line” control actions aimed to reduce the level of the exposure to dust of the workers, as for example: i) modification of aspirating devices operating condition, change of filtering cleaning sequence, etc. . The more severe are the environmental conditions, in terms of dust presence (in quantity and quality) more difficult is to utilize efficient sampling devices. Detection devices, in fact, tend to become “blind” to dust as dust presence increases, on the other hand severe dust production conditions is exactly the case where control strategies have to be applied to realize safer conditions for the workers. In this paper the possibility to utilize a new logic to perform an “on-line” airborne dust sampling and analysis utilizing imaging is described with particular reference to dusts flowing in a duct after the caption and before their abatement by classical mechanical filtering. The study was particularly addressed to define, design and implement a logic able to extract those parameters affecting airborne dust behavior with respect to its efficient abatement. All dust sampling was performed directly in an industrial plant where tests were carried out in a controlled environment.

Proceedings Article | 3 May 2004 Paper

Digital-imaging-based spectrometry applied to ceramic glass inspection

Giuseppe Bonifazi, Laura D'Aniello, Silvia Serranti

Proceedings Volume 5303, (2004) https://doi.org/10.1117/12.524788

KEYWORDS: Glasses, Ceramics, Reflectivity, Spectroscopy, Surface finishing, Near infrared, Spectrophotometry, Cameras, Visible radiation, Light sources and illumination

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Proceedings Article | 30 March 2004 Paper

Digital-imaging-based spectrophotometric techniques for soil pathogen monitoring and detection

Giuseppe Bonifazi, Paolo Menesatti

Proceedings Volume 5271, (2004) https://doi.org/10.1117/12.515553

KEYWORDS: Soil science, Reflectivity, Light sources and illumination, Agriculture, Signal processing, Digital imaging, Statistical analysis, Spectrophotometry, Charge-coupled devices, Digital signal processing

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Proceedings Article | 28 May 2003 Paper

Imaging techniques applied to quality control of civil manufactured goods obtained starting from ready-to-use mixtures

Giuseppe Bonifazi, Federica Castaldi

Proceedings Volume 5014, (2003) https://doi.org/10.1117/12.473128

KEYWORDS: Cements, Manufacturing, Control systems, Image processing, Particles, Image analysis, Statistical analysis, Digital imaging, Solids, Image enhancement

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Proceedings Article | 22 May 2003 Paper

Ornamental stone finished product aesthetic inspection and characterization through a digital spectrophotometric approach

Giuseppe Bonifazi, Stefano Marinelli

Proceedings Volume 5011, (2003) https://doi.org/10.1117/12.473969

KEYWORDS: Polishing, Surface finishing, Spectroscopy, Reflectivity, Reflection, Abrasives, Inspection, Minerals, Fiber optics, Manufacturing

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Proceedings Article | 22 May 2002 Paper

Fractal-based morphological image processing approach to analyzing complex structures characterized by closed domains

Giuseppe Bonifazi

Proceedings Volume 4667, (2002) https://doi.org/10.1117/12.467995

KEYWORDS: Fractal analysis, Particles, Solids, Image processing, Algorithm development, Image analysis, Image segmentation, Image resolution, Systems modeling, Glasses

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Fractal geometry concerns the study of non-Euclidean geometrical figures generated by a recursive sequence of mathematical operations. These figures show self-similar features in the sense that their shape, at a certain scale, is equal to, or at least 'similar' to, the same shape of the figure at a different scale or resolution. This property of scale invariance often occurs also in some natural events. The basis of the method is the very comparison of the space covering of one of those geometrical constructions, the 'Sierpinski Carpet,' and the particles location and size distribution in the portion of surface acquired in the images. Fractal analysis method, consists in the study of the size distribution structure and disposition modalities. Such an approach was presented in this paper with reference to the characterization of airborne dust produced in working environment through the evaluation of particle size disposition and distribution over a surface. Such a behavior, in fact, was assumed to be strictly correlated with 1) material surface physical characteristics and 2) on the modalities by which the material is 'shot' on the dust sample holder (glass support). To get this goal, a 2D-Fractal extractor has been used, calibrated to different area thresholding values, as a result binary sample image changes, originating different fractal resolutions plotted for the residual background area (Richardson plot). Changing the lower size thresholding value of the 2D-Fractal extractor algorithm, means to change the starting point of fractal measurements; in such way, it has been looked for possible differences of powders in the lower dimensional classes. The rate by which the lowest part of the plot goes down to residual area equal to zero, together with fractal dimensions (low and high, depending on average material curve) and their precision (R²) of 'zero curve' (Richardson Plot with area thresholding value equal to zero, i.e. whole fractal distribution), can be used as criterions to classify the materials and working actions producing dust. For the intrinsic structure of the procedure and algorithms the proposed 2D Fractal Analysis, originally developed for particles, can be successfully applied to many others sectors as biology (cell and tissues), medical imaging, food industry, advanced materials characterization, nanoparticles, composite materials, alloys, etc.

Proceedings Article | 5 April 2002 Paper

Combined imaging and neural-network-based approach in solid waste sorting

Stefano Alunni, Giuseppe Bonifazi, Alessandro de Carli, Paolo Massacci

Proceedings Volume 4668, (2002) https://doi.org/10.1117/12.461674

KEYWORDS: Particles, Solids, Error analysis, Image processing, Image segmentation, Neural networks, Digital image processing, Image resolution, Logic, Image classification

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Showing 5 of 63 publications

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SC511: Applied Imaging Based Morphology

This course provides the attendee with basic working knowledge to perform morphological and morphometrical based characterization of closed domains (objects, cells, biological tissues, particles, etc.). It gives the fundamentals of digital morphology and shows its great potential for use in many research and industrial sectors. Case studies are presented and evaluated. Attendees will become fluent in the selection and design of analytical tools and architectures used to perform a morphological and morphometrical characterization of electronic images content.

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