Keyblock: An approach for content-based image retrieval

We propose a new framework termed Keyblock for content-based image retrieval, which is a generalization of the text-based information retrieval technology in the image domain. In this framework, methods for extracting comprehensive image features are provided, which are based on the frequency of representative blocks, termed keyblocks, of the image database. Keyblocks, which are analogous to index terms in text document retrieval, can be constructed by exploiting the vector quantization (VQ) method which has been used for image compression. By comparing the performance of our approach with the existing techniques using color feature and wavelet texture feature, the experimental results demonstrate the effectiveness of the framework in image retrieval.