In this paper, An Automatic Multilevel Thresholding Method for Image segmentation is proposed based on Discrete Wavelet Transforms and Genetic Algorithm. We have combined Genetic Algorithm with DWT to make Segmentation faster and adequate results. First the length of the histogram is reduced by using DWT. Using this Reduced Histogram, the number of Thresholds and Threshold Value are determined ...

We implement structural risk minimization and cross-validation in order to optimize kernel and parameters of a support vector machine (SVM) and multiclass SVM-based image classifiers, thereby enabling the diagnosis of genetic abnormalities. By thresholding the distance of patterns from the hypothesis separating the classes we reject a percentage of the miss-classified patterns reducing the expe...

-In this paper, we show that Otsu's image thresholding, Kittler and Illingworth's minimum error thresholding, and Huang and Wang's fuzzy thresholding methods can be derived under a similar mathematical formulation. The difference among the three methods is the choice of different weighting functions for computing a criterion function that can be considered as a weighted summation of the image g...

Computed tomography technology is one of the important technology techniques, which shows the inside part of the human body through scanning the specific area. FDT Technique aims to augment the precision of the CT image thresholding by implementing an advanced thresholding approach from four different directions. Based on the FDT technique, the foreground and back ground pixel values of the adj...

Image thresholding and edge detection are crucial in image processing and understanding. In this chapter, the authors propose a hierarchical multilevel image thresholding method for edge information extraction based on the maximum fuzzy entropy principle. In order to realize multilevel thresholding, a tree structure is used to express the histogram of an image. In each level of the tree structu...

This paper proposes a global multi-level thresholding method for image segmentation. As a criterion for this, the traditional method uses the Shannon entropy, originated from information theory, considering the gray level image histogram as a probability distribution, while we applied the Tsallis entropy as a general information theory entropy formalism. For the algorithm, we used the artificia...

-A relative entropy based approach to image thresholding was proposed recently. It was demonstrated that this method was successful for image thresholding. Relative entropy is a member of the class of Ali-Silvey distance measures. In this paper we generalize the relative entropy based approach and present image thresholding algorithms based on the class of Ali-Silvey distance measures. A number...