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Pattern Analysis for detecting Pathology Using Haralick Texture Features


S. Simonthomas


Vol. 15  No. 11  pp. 53-57


Cancer is a diseases that characterized by out of control cell growth. There are different types of cancer disease, and each is classified by the type of cell that is initially affected by the disease. Cancer harms the body when damaged cells divide uncontrollably to form lumps or masses of tissue called tumours. In this paper haralick texture features used to detect the cancer disease by using a segmented images of cell tissues. it characterize the biomedical images in pattern recognization a tissue image and this tissue quanti?cation based on the pattern classifications. then the given tissue image satisfies the haralick texture means it is a normal tissue. the calculation is based on pixel values in an image. The accuracy has been calculated based on SVM classifier. Working with the tissue images, our experiments gives that the proposed a 95% accuracy compare to the existing one. and the accuracies for the tissue image quanti?cation.


Cancer diagnosis, GLCM, Haralick Texture features, SVM, structural pattern recognition.