KEYWORDS: RGB color model, Image segmentation, CMYK color model, Fuzzy logic, Tissues, Image processing, Color image processing, In vivo imaging, Digital image processing, Microscopes
This paper presents two image techniques for morphometric evaluation. The first one improve the color contrast employing color equalization and borders are identified by using splines. The second one is a semiautomatic method that use fuzzy color thresholding. The second technique will provide the basis of a future automatic method. These techniques are experimentally validated measuring neoformed vessels on histological sections of mice's thigh.
Tuberculosis (TB) and other mycobacteriosis are serious illnesses which control is mainly based on presumptive diagnosis. Besides of clinical suspicion, the diagnosis of mycobacteriosis must be done through genus specific smears of clinical specimens. However, these techniques lack of sensitivity and consequently clinicians must wait culture results as much as two months. Computer analysis of digital images from these smears could improve sensitivity of the test and, moreover, decrease workload of the micobacteriologist. Bacteria segmentation of particular species entails a complex process. Bacteria shape is not enough as a discriminant feature, because there are many species that share the same shape. Therefore the segmentation procedure requires to be improved using the color image information. In this paper we present two segmentation procedures based on fuzzy rules and phase-only correlation techniques respectively that will provide the basis of a future automatic particle' screening.
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