DETECTION AND CLASSIFICATION OF BREAST CANCER USING SUPPORT VECTOR MACHINE AND ARTIFICIAL NEURAL NETWORK USING CONTOURLET TRANSFORM
Abstract
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The technique of image processing is applied to diagnose breast cancer from digital mammogram image. The proposed work uses Contourlet transform to decompose the given gray-scale image. The spatial (textual and statistical) features are been extracted along with frequency domain coefficients. GLCM is the method used for extracting the feature values. Classification of image using support vector machine or artificial neural network classifiers is performed.

Authors
Soumya Hundekar, Saritha Chakrasali
BNM Institute of Technology, India

Keywords
Mammographic Images, Support Vector Machine (SVM), Feature Extraction, Contourlet Transform (CT), Gray Level Co-occurrence Matrix (GLCM), Artificial Neural Network (ANN)
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Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 9 , Issue: 3 , Pages: 1966-1971 )
Date of Publication :
February 2019
Page Views :
165
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