A Study of Feature Extraction and Selection Techniques for Brain Abnormalitites Classification
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