SamMatch: a flexible and efficient sampling-based image retrieval technique for large image databases

The rapid growth of digital image data increases the need for efficient and effective image retrieval systems. Such systems should provide functionality that tailors to the user's need at the query time. In this paper, we propose a new image retrieval technique that allows users to control the relevantness of the results. For each image, the color contents of its regions are captured and used to compute similarity. Various factors, assigned automatically or by the user, allow high recall and precision to be obtained. We implemented the proposed technique for a large database of 16,000 images. Our experimental results show that this technique is not only space-time efficient but also more effective than recently proposed color histogram techniques.