Acceleration of similarity-based partial image retrieval using multistage vector quantization

We propose a new method for quick and accurate partial image retrieval from a huge number of images based on a predefined distance measure. The proposed method utilizes vector quantization (VQ) on multiple layers, namely color, block, and feature layers. This can greatly reduce the amount of calculation needed for partial image retrieval. Experiments indicate that the proposed method can detect partial images that are similar to queries through 1000 images within 4 seconds. This is approximately 30 times faster than the method to which multistage VQ is not applied.