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The early detection of the lung cancer is a challenging problem, due to the structure of the cancer cells. This paper presents two segmentation methods, Hopfield Neural Network (HNN) and a Fuzzy C-Mean (FCM) clustering algorithm, for segmenting sputum color images to detect the lung cancer in its early stages. The manual analysis of the sputum samples is time consuming, inaccurate and requires intensive...
The Image segmentation plays an important role in computer vision and image processing areas. In this paper, the use of color segmentation for segmenting acute leukemia images is proposed. The segmentation technique segments each leukemia image into two regions: blast and background. In our approach, the segmentation is based on HSI and RGB color space. The performance comparison between the segmentation...
Infrared thermography is recently widely accepted as a medical diagnostic tool. Thermographs are acquired for the whole body or the region of interest. Thermographs are processed for abnormality detection and quantification. As temperature variations are not normally visible to naked eye it is necessary to develop and analyze the feature extraction algorithms for abnormality detection. This paper...
The recognition of tongue image is one of the essential contents for automatic diagnosis of tongue information. The identification of tongue quality and coating is an important procedure in the tongue diagnosis, and it is also the premise for analyzing the color of tongue quality and coating and its texture characteristics in the later stage. This paper employs "division-merging method"...
It is fundamental work for objective tongue inspection to accurately segment tongue body from original image. This paper presents a new color tongue image segmentation algorithm based on HSI model. The original image was converted to HSI space firstly. Then it was segmented by threshold value of hue and intensity component before it was converted to binary image. Finally the sequential algorithm was...
Image segmentation, which is the first essential and fundamental issue in the image analysis and pattern recognition, is a classical difficult problem in the image processing. The color images, which possess more visual information than the gray images do, have aroused more and more attentions. In the medical imaging system, according to the different absorbency of different tissues, the staining...
This paper presents a new algorithm using anisotropic diffusion and mean shift applied in the color image. It is shown how segmentation can benefit from splitting color signals into chromatic and achromatic channels and separately smoothing them through anisotropic diffusion. The result of diffusion is segmented by mean shift techniques and their combination yields the final image partition into homogeneous...
We present a class of simple algorithms for color image segmentation based on the nearest neighbor (1-NN) decision rule. The feature vector for each pixel in the image is constructed from color components in HSI space. Since processing all pixels with 1-NN rule is time-consuming, we decided that only some "crate" pixels must be classified with 1-NN, while the others can then be labeled according...
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