Image retrieval method using visual query suggestion and relevance feedback

Query suggestion is an effective human-computer interaction (HCI) approach in information retrieval. According to human vision system, the image retrieval method using visual query suggestion (VQS) can provide a friendly query interface to solve the query ambiguity problem. In this paper, the content-based image retrieval (CBIR) system is realized first. Human-computer interaction used VQS to obtain users' intention. In this step, user submitted a query keyword to the system. VQS is utilized to provide a list of suggestions, each containing a keyword and a collection of representative images. If the user selects one of the image suggestions, this image will be viewed as the key image. Then CBIR system will retrieve the image sets to return the similar images based on the similarity of image features. In relevance feedback, user scored each returned image by the slider to optimize retrieval results. A friendly query interface is designed to carry out HCI in our system and the experimental result shows the proposed method can improve the average recall and precision efficiently.