PERFORMANCE ANALYSIS OF TEXTURE IMAGE RETRIEVAL FOR CURVELET, CONTOURLET TRANSFORM AND LOCAL TERNARY PATTERN USING MRI BRAIN TUMOR IMAGE

Texture represents spatial or statistical repetition in pixel intensity and orientation. Brain tumor is an abnormal cell or tissue forms within a brain. In this paper, a model based on texture feature is useful to detect the MRI brain tumor images. There are two parts, namely; feature extraction process and classification. First, the texture features are extracted using techniques like Curvelet transform, Contourlet transform and Local ternary pattern (LTP). Second, the supervised learning algorithm like Deep neural network (DNN) is used to classify the brain tumor images. The Experiment is performed on a collection of 1000 brain tumor images with different orientations. Experimental results reveal that contourlet transform technique provides better than curvelet transform and Local ternary pattern.