Multi Stage Knowledge Base for Content Based Image Retrieval with Efficient Feedback
Multimedia images are increasing day to day. So retrieving images in large scale database is hectic. To be more profitable, relevance feedback techniques were incorporated into CBIR such that more precise results can be obtained by taking user's feedbacks into account. However, existing relevance feedback-based CBIR methods usually request a number of iterative feedbacks to produce refined search results, especially in a large-scale image database. This is impractical and inefficient in real applications. This paper addressing image retrieval using an efficient algorithm with encompasses relevance feedback from the user. This mining algorithm majorly focuses on knowledge based and graph based navigation pattern methods.