Fusion Method Based on Association Rules for Image Retrieval

Image mining deals with the extraction of image patterns from a large collection of images. Clearly, image mining is different from low-level computer vision and image processing techniques because the focus of image mining is in extraction of patterns from large collection of images, whereas the focus of computer vision and image processing techniques is in understanding and/or extracting specific features from a single image. In image re- ranking, it needs first to perform the search based on the text query. Then the returned list of images is reordered according to the visual features similarity. The retrieving method in this paper utilizes the fusion of the images- multimodal information (textual and visual) which is a recent trend in image retrieval researches. It combines the techniques like association rule mining, SVM classifier and saliency map detection for retrieving semantically related images. Proposed method trying to enhance the image retrieval performance by fusing i. e. textual and visual features for retrieving and narrow the semantic gap problem