Performance Analysis of Coiflet Wavelet and Moment Invariant Feature Extraction for CT Image Classification using SVM

Feature Extraction is the process to extract image features to a distinguishable extent. Information extracted from images such as color, texture and shape are known as feature vectors. Using multiple feature vectors to describe an image during retrieval process increases the accuracy when compared to the retrieval using single feature vector. The objective of this paper is to analyze the performance of coiflet wavelet and Moment Invariant (MI) feature extraction methods and to evaluate the classification accuracy using Support Vector Machines (SVM) with Radial Basis Function kernel (RBF). Experiments were conducted on CT scan images of head, lung and stomach and the performance are investigated.