Publish In |
International Journal of Advances in Science, Engineering and Technology(IJASEAT)-IJASEAT |
Journal Home Volume Issue |
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Issue |
Volume-5,Issue-1, Spl. Iss-2 ( Feb, 2017 ) | |||||||||
Paper Title |
A Study of Feature Extraction and Selection Techniques for Brain Abnormalitites Classification | |||||||||
Author Name |
Rupal Snehkunj, Ashish Jani | |||||||||
Affilition |
Shree Ramkrishna Institute of Computer Education & Applied Sciences, Surat, Gujarat. India,Department of Computer Science, S.K. Patel Institute of Management & Computer Studies, Gandhinagar,Gujarat, India | |||||||||
Pages |
44-46 | |||||||||
Abstract |
In this paper, we present a comparative study of various techniques which have been proposed for feature extraction and selection of brain abnormalities in MRI data. The techniques include GLCM, PCA, and LDA which are reviewed in this paper. In GLCM, it calculates the co-occurrence matrix of an image which are used to distinguish between normal and abnormal patient whereas PCA(principal component analysis) and LDA(linear discriminant analysis) are used to reduce the number of features which are retrieved after applying GLCM Simulation is done in MATLAB 2013a and results for the techniques are discussed.. Keywords- GLCM, PCA,LDA, brain abnormalities | |||||||||
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