Content-Based Image Retrieval with HSV Color Space and Texture Features

An image retrieval system is presented, which used HSV color space and wavelet transform approach for feature extraction. Firstly, we quantified the color space in non-equal intervals, then constructed one dimension feature vector and represented the color feature. Similarly, the work of texture feature extraction is obtained by using wavelet. Finally, we combine color feature and texture feature based on wavelet transform. A method of multi features retrieval is provided. The image retrieval experiments indicated that visual features were sensitive for different type images. The color features opted to the rich color image with simple variety. Texture feature opted to the complex images. At the same time, experiments reveal that texture feature based on wavelet transform has better effective performance and stability.