Research Journal of Applied Sciences

Year: 2014
Volume: 9
Issue: 2
Page No. 110 - 118

Classification of Feature Extracted, Selected and Segmented Mammogram Image Using Hybrid Algorithm-Monkey Search Optimization (MSO) and Support Vector Machine (SVM)

Authors : S. Kanimozhi Suguna and S. Uma Maheswari

Abstract: Classification is most important for analyzing the mammograms of breast cancer. This study proposes a different approach based on Metaheuristic Algorithm is presented for classifying the mammogram image. The foraging behavior of monkey is optimized as Monkey Search Optimization (MSO) which is the subset of the metaheuristic algorithm. Feature extracted image is given as input for the process of classification. To solve complex problems by cooperation the behaviors are considered. Several algorithms based on population-based metaheuristic algorithms were introduced in the literatures to solve different problems like optimization problems. This is the new technique proposed for classifying the mammogram images. Results are presented based on simulation made with the implementation in MATLAB which is tested on the images of MIAS database.

How to cite this article:

S. Kanimozhi Suguna and S. Uma Maheswari, 2014. Classification of Feature Extracted, Selected and Segmented Mammogram Image Using Hybrid Algorithm-Monkey Search Optimization (MSO) and Support Vector Machine (SVM). Research Journal of Applied Sciences, 9: 110-118.

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