Content-Based Image Retrieval Using Color Space Transformation and Wavelet Transform

Retrieval by image content has received great attention in the last decades. In this paper, a content-based image retrieval method based on the wavelet transform is proposed. Due to the superiority in multiresolution analysis and spatial-frequency localization, the wavelet transform is applied to extract low-level features from the images. In the image database establishing phase, each image is first transformed from the standard RGB color space to the YUV space; then Y component of the image is further transformed to the wavelet domain. In the image retrieving phase, the system compares the most significant wavelet-subbands of the Y component of the query image and those of the images in the database and find out good matches. The feature sets derived from the color space transformation and the wavelet transform can reduce the processing time without sacrificing the retrieving accuracy. We have performed experiments on a thousand images database and our results show a high retrieval accuracy.