摘要：The current image retrieval systems are successful in retrieving images, using keyword based approaches. However, they are incapable to retrieve the images which are context sensitive and annotated inappropriately. Content-Based Image Retrieval (CBIR) aims at developing techniques that support effective searching and browsing of large image repositories, based on automatically derived image features. The current CBIR systems suffer from the semantic gap. Though a user feedback is suggested as a remedy to this problem, it often leads to distraction in the search. To overcome these disadvantages, we propose a novel interactive image retrieval system, integrating text and image content to enhance the retrieval accuracy. Also we propose a novel refining search algorithm to narrow down the search further from the retrieved images. The experimental results demonstrate the performance of the proposed system.
关键词：Color histogram; color quantization; image descriptor; refining search;region-based segmentation and term feedback.
