Vector Quantization Based Index Cube Model for Image Retrieval

We propose a Vector quantization (VQ) based index cube model for content based image retrieval. VQ captures the pixel intensity and the spatial information of the image blocks. An indexing and retrieval algorithm is implemented and different similarity measures are evaluated with the precision and recall curves. It can be used for content based image retrieval in image databases using the incremental codebook generation process. The index is scalable as new images can be easily appended to the index. The retrieval time is reduced as there is no processing of the query image before retrieval.