International Journal of Engineering and Technology

Feature extraction is an important step in Computer Assisted Diagnosis of brain abnormalities using Magnetic Resonance Images (MRI).Feature Extraction is the process of reducing the size of image data by obtaining necessary information from the segmented image. The visual content of a segmented image can be captured using this process. From the extracted features it is possible to demarcate between normal and abnormal brain MRI. The reliability of the classification algorithm depends on segmentation method and extracted features. In this work texture features are extracted using Gray Level Co-occurrence Matrix (GLCM) and shape features are extracted using connected regions. Images with malignant tumor, benign tumor and normal brain have different features. This variation in feature values is useful in classification of MR images. The features thus obtained will be given to a classifier for training and testing.