DETECTION AND CLASSIFICATION OF BREAST CANCER USING SUPPORT VECTOR MACHINE AND ARTIFICIAL NEURAL NETWORK USING CONTOURLET TRANSFORM

ICTACT Journal on Image and Video Processing ( Volume: 9 , Issue: 3 )

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)

Published By
ICTACT
Published In
ICTACT Journal on Image and Video Processing
( Volume: 9 , Issue: 3 )
Date of Publication
February 2019
Pages
1966-1971
Page Views
335
Full Text Views
3

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