Image retrieval using both color and texture features ABSTRACT: This paper has a further exploration and study of visual feature extraction. According to the HSV (Hue, Saturation, Value) color space, the work of color feature extraction is finished, the process is as follows: quantifying the color space in non-equal intervals, constructing one dimension feature vector and representing the color feature by cumulative histogram. Similarly, the work of texture feature extraction is obtained by usinggray-level co-occurrence matrix (GLCM) or color co-occurrence matrix (CCM). Through the quantification of HSVcolor space, we combine color features and GLCM as well as CCM separately. Depending on the former, imageretrieval based on multi-feature fusion is achieved by using normalized Euclidean distance classifier. Through theimage retrieval experiment, indicate that the use of color features and texture based on CCM has obvious advantage. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Fast LMS/Newton Algorithms for Stereophonic Acoustic Echo Cancellation An Adaptive Steganographic Technique Based on Integer Wavelet Transform