Comparison of different feature extraction techniques in content-based image retrieval for CT brain images

Content-based image retrieval (CBIR) system helps users retrieve relevant images based on their contents. A reliable content-based feature extraction technique is therefore required to effectively extract most of the information from the images. These important elements include texture, colour, intensity or shape of the object inside an image. CBIR, when used in medical applications, can help medical experts in their diagnosis such as retrieving similar kind of disease and patientpsilas progress monitoring. In this paper, several feature extraction techniques are explored to see their effectiveness in retrieving medical images. The techniques are Gabor transform, discrete wavelet frame, Hu moment invariants, Fourier descriptor, gray level histogram and gray level coherence vector. Experiments are conducted on 3,032 CT images of human brain and promising results are reported.