Image retrieval using both color and texture features

• Published in: 2009 International Conference on Machine Learning and Cybernetics Vol. 4; pp. 2228 - 2232
• Main Author: Fan-Hui Kong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2009
• Subjects: CCM; Content based retrieval; Cybernetics; Equations; Feature extraction; GLCM; Humans; Image color analysis; Image retrieval; Machine learning; Quantization; Space technology
• ISBN: 9781424437023; 1424437024
• ISSN: 2160-133X
• DOI: 10.1109/ICMLC.2009.5212186

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 using gray-level co-occurrence matrix (GLCM) or color co-occurrence matrix (CCM). Through the quantification of HSV color space, we combine color features and GLCM as well as CCM separately. Depending on the former, image retrieval based on multi-feature fusion is achieved by using normalized Euclidean distance classifier. Through the image retrieval experiment, indicate that the use of color features and texture based on CCM has obvious advantage.