Paper
15 November 2002 Segmentation, autofocusing and signagture extraction of tuberculosis sputum images
Manuel G. Forero-Vargas, Filip Sroubek, Josue Alvarez-Borrego, Norberto Malpica, Gabriel Cristobal, Andres Santos, Luis Alcala, Manuel Desco, Leon Cohen
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Abstract
Bacteria segmentation of particular species entails a challenging process. Bacteria shape is not enough as a discriminant feature, because there are many species that share the same shape. We present here two methods for tuberculosis image segmentation using the chromatic information. The first method is based on fuzzy segmentation of the color images based on the information that it is entailed in each separate chromatic histogram. The second method is a simple color filtering account by comparison of the inverse of the yellowish stained bacteria (blue channel) with the product of the other two chromatic channels. The third method is based on the extraction of image signatures by projecting logarithmic-polar mappings onto 1D vectors. This representation provides a very compact description of all image aspects, including shape, texture and color. An achromatic segmentation method is also presented based on the use of gray-level morphological operators only to the green channel. Finally we present the results of different autofocusing algorithms of stained tuberculosis images.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Manuel G. Forero-Vargas, Filip Sroubek, Josue Alvarez-Borrego, Norberto Malpica, Gabriel Cristobal, Andres Santos, Luis Alcala, Manuel Desco, and Leon Cohen "Segmentation, autofocusing and signagture extraction of tuberculosis sputum images", Proc. SPIE 4788, Photonic Devices and Algorithms for Computing IV, (15 November 2002); https://doi.org/10.1117/12.451665
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Cited by 19 scholarly publications.
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KEYWORDS
Image segmentation

Bacteria

Colorimetry

Image processing

Luminescence

Optical filters

Color image processing

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