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A novel method of image segmentation based on gradient inhibiting PCNN (GIPCNN) is presented in this paper. At first, based on the characteristic of optic sensing on the gradient inhibiting, we improved the model of Pulse-Coupled Neural Networks. Then, the adaptive determination of PCNN parameters is presented and the method of determining the optimal result from segmented image sequences is introduced...
Counting of different classes of white blood cells in bone marrow smears can give pathologists valuable information regarding various hematological disorders. For automation imaging analysis techniques, precise segmentation of white blood cells is quite challenging due to the complex contents in bone marrow smears. Far more different from traditional color imaging analysis methods, we introduced multispectral...
A new Hough-based algorithm termed segment Hough transform (SHT) is proposed to detect the curve in the binary image. The segment-transform, which is the main idea of the novel approach, makes the curve detection very efficient. Thanks to the chain code termed angle chain code (ACC) as well as the modified direction measurement, the segmentation operation is also considerably fast and precise. Compared...
This paper presents a new method of dorsal hand vein images segmentation based on local thresholding using grayscale morphology. The images, captured by near- infrared CMOS cameras, have poor contrast, speckling noise and non-uniform lighting. After the preprocessing these images normalized, we use dilation and erosion operations to calculate the local thresholding and segment to get the binary images...
In this paper, a complete procedure is proposed to analyze and classify the texture of an image based Bayesian network classifiers. We apply this procedure in the residential areas detection. A simple case of Bayesian network called naive Bayes classifier is used to learn the positive and negative samples and to infer about the unknown regions. In this paper, each texture feature vector is labeled...
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