The wide scale inspection of extended technical components with respect to the recognition of typical surface features (shape, texture, roughness) needs the combined application of different measurement techniques with new tools for the consistent analysis and description of the measuring results. The new concept of scaleable topometry meets the demands of wide scale surface topometry. Controlled by the evaluation of scale-independent surface features based on fractal geometry, different measurement techniques with subsequent lateral and depth resolution are applied to the surface. The result is a complete description of the surface covering a wide scale taking into account special regions of interest. The choice and orientation of the special measurement technique is supported by a new feature extraction method called the fractal pyramid. The advantages of the new concept are demonstrated on several technical components.
In this paper we present the first steps to an algorithm for effective compression of digital holograms. This algorithm is based on the properties of the electromagnetic field that generates the holograms. The investigation of the underlying physical behavior allows us a better reduction of the number of bits needed to compress the data. We show that the quantization in the frequency domain as contained in the extended JPEG compression is suitable for high quality compression of holograms. We present the application of this approach to holograms with low space-bandwidth products and perform a generalization to typical holograms with high space-bandwidth products. Our tests using simulated and real world holograms from different origins show approximately the same performance on the same levels of compression. This performance is better concerning the quality of the data compared to the one of the standard JPEG implementation and can be improved concerning the file size. While the visual impression of the intensity reconstruction is good even for 2bit compression, the reconstruction of the phase for higher compression ratios shows remarkable errors. In the future we want to better adopt our approach to the extended JPEG standard based in the way that we use 8x8 clusters instead of the whole image for quantization. This gives hope to further increase the reconstruction quality and the compression ratio in the future.
The resolution of digital holography as an optical imaging system is described by the point spread function of the system. The point spread function of double aperture digital holography is determined. It promises the possibility of a resolution increase by the concept of synthetic apertures. First results of numerically reconstructed wave fields from synthetic digital holograms combined of two single holograms are shown. Furthermore an experimental method for the exact determination of the mutual CCD position and orientation is presented.
Reliable real-time surface inspection of extended surfaces with high resolution is needed in several industrial applications. With respect to an efficient application to extended technical components such as aircraft or automotive parts, the inspection system has to perform a robust measurement with a ratio between depth resolution and lateral extension of less than 10–6. This ratio is at least 1 order beyond the solutions that are offered by existing technologies. The concept of scaled topometry consists of a systematic combination of different optical measurement techniques with overlapping ranges of resolution systematically to receive characteristic surface information with the required accuracy. In such a surface inspection system, an active algorithm combines measurements on several scales of resolution and distinguishes between local fault-indicating structures with different extensions and global geometric properties. The first part of this active algorithm finds indications of critical surface areas in the data of every measurement and separates them into different categories. The second part analyzes the detected structures in the data with respect to their resolution, and decides whether a further local measurement with a higher resolution has to be performed. The third part positions the sensors and starts the refined measurements. The fourth part finally integrates the measured local dataset into the overall data mesh. We have constructed a laboratory setup capable of measuring surfaces with extensions up to 1500×1000×500 mm3 (in x, y, and z directions, respectively). Using this measurement system we are able to separate the fault-indicating structures on the surface from the global shape, and to classify the detected structures according to their extensions and characteristic shapes simultaneously. The level of fault-detection probability is applicable by input parameter control.
In this paper the dynamic processing of interferometric fringe patterns obtained by real-time optical measurement methods like holographic interferometry is shown. A hologram of the tested component is superimposed with the hologram of the stressed component. The achieved fringe patterns vary according to the degree of stress applied. To evaluate these varying fringe patterns in real time, dynamic filtering is required. A hybrid opto-electronic sytem with a digital image processing and optical correlation module based on liquid-crystal spatial light modulators gives us the possibility to use dynamic filters and input images. In order to process interferometric fringes the adaptive wavelet transformation is applied.
In this paper the dynamic processing of interferometric fringe patterns obtained by real-time optical measurement methods like holographic interferometry is shown. A hologram of the tested component is superimposed with the hologram of the stressed component. The achieved fringe patterns vary according to the degree of stress applied. To evaluate these varying fringe patterns in real time, dynamic filtering is required. A hybrid opto-electronic system with a digital image processing and optical correlation module based on liquid-crystal spatial light modulators gives us the possibility to use dynamic filters and input images. In order to process interferometric fringes the adaptive wavelet transformation is applied.
We will show two methods of dynamic filtering. Firstly a static filter is used to process varying fringe patterns. With this method changes of features in the fringe patterns can be observed correlating to changes of stress applied on the tested component. Another application of dynamic filtering uses a static input image and dynamic filters. This method is used for the classification of interferometric fringe patterns. A set of different wavelet filters is applied to the input image using the ability of the spatial light modulator to display images in video frame rates. Comparing the wavelet filters and the output images it is possible to assign the fringe patterns to a fault class.
KEYWORDS: Inspection, Sensors, Tolerancing, Fractal analysis, Wavelets, Data integration, Detection and tracking algorithms, Optical testing, Assembly tolerances, Process control
Reliable real-time surface inspection of extended surfaces with high resolution is needed in several industrial applications. With respect to an efficient application to extended technical components such as aircraft or automotive parts, the inspection system has to perform a robust measurement with a ratio of less then 10-6 between depth resolution and lateral extension. This ratio is at least one order beyond the solutions that are offered by existing technologies. The concept of scaled topometry consists of arranging different optical measurement techniques with overlapping ranges of resolution systematically in order to receive characteristic surface information with the required accuracy. In such a surface inspection system, an active algorithm combines measurements on several scales of resolution and distinguishes between local fault indicating structures with different extensions and global geometric properties. The first part of this active algorithm finds indications of critical surface areas in the data of every measurement and separates them into different categories. The second part analyses the detected structures in the data with respect to their resolution and decides whether a further local measurement with a higher resolution has to be performed. The third part positions the sensors and starts the refined measurements. The fourth part finally integrates the measured local data set into the overall data mesh. We have constructed a laboratory setup capable of measuring surfaces with extensions up to 1500mm x 1000mm x 500mm (in x-, y- and z-direction respectively). Using this measurement system we will be able to separate the fault indicating structures on the surface from the global shape and to classify the detected structures according to their extensions and characteristic shapes simultaneously. The level of fault detection probability will be applicable by input parameter control.
The detection and classification of faults is a major task for optical nondestructive testing in industrial quality control. Interferometric fringes, obtained by real-time optical measurement methods, contain a large amount of image data with information about possible defect features. This mass of data must be reduced for further evaluation. One possible way is the filtering of these images applying the adaptive wavelet transform. The wavelet transform has been proved to be a capable tool in the detection of structures with definite spatial resolution. In this paper it is shown the extraction and classification of disturbances in interferometric fringe patterns, the application of several wavelet functions with different parameters for the detection of faults, and the combination of wavelet filters for fault classification. Furthermore the implementation of complex valued wavelet filters and correlation filters is shown. We will present an algorithm to classify interferometric fringe patterns. In order to achieve real-time processing a hybrid opto-electronic system with a digital image processing and an optical correlation module is favored. The calculated wavelet filters are implemented into the optical correlator system that is based on liquid-crystal spatial light modulators. So, all discussed items were verified experimentally in the optical setup.
The detection and classification of faults is a major task for optical nondestructive testing in industrial quality control. Interferometric fringes, obtained by real-time optical measurement methods, contain a large amount of image data with information about possible defect features. This mass of data must be reduced for further evaluation. One possible way is the filtering of these images applying the adaptive wavelet transform, which has been proved to be a capable tool in the detection of structures with definite spatial resolution. In this paper we show the extraction and classification of disturbances in interferometric fringe patterns, the application of several wavelet functions with different parameters for the detection of faults, and the combination of wavelet filters for fault classification. Examples for fringe patterns of known and varying fault parameters are processed showing the trend of the extracted features in order to draw conclusions concerning the relation between the feature, the filter parameter, and the fault attributes. Real-time processing was achieved by importing video sequences in a hybrid opto-electronic system with digital image processing and an optical correlation module. The optical correlator system is based on liquid-crystal spatial light modulators, which are addressed with image and filter data. Results of digital simulation and optical realization are compared.
The fast and reliable localization and classification of fault indicating fringe patterns in interferometric images is a major task in holographic non-destructive testing. For the purpose of feature extraction from gray value images, wavelet transformation has proved to be a suitable tool. In contrast to the Fourier transformation the local feature information will be preserved and furthermore the applied transforming wavelet can be adapted--under certain constraints--to the given problem.
The idea of scaled topometry is to organize systematically different optical measurement techniques with overlapping ranges of resolution in order to receive highly resolved surface information in a wide range of scales. In such a surface inspection system, measurements on different scales of resolution have to be combined by a discrimination algorithm which should be sensitive on faults independent on the scale of resolution. Starting from a global measurement with low resolution certain critical areas have to be detected in which a refined measurements has to be performed. This process of detection and refinement has to be repeated on different scales. The task of the discrimination algorithm should be the detection of critical structures and the determination of the necessary order of refinement in the resolution. For the reason of scale- independence a classical approach using the surface roughness is not suitable.
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