An image retrieval method with multi-instance learning

In this paper, a multi-instance learning based CBIR (content-based image retrieval) approach is presented, and multi-instance learning method is applied in CBIR, in order to deal with the inherent ambiguity of images. First of all the whole image is regards as a multi-instance bag, secondly the image is partitioned into multi-regions by using adaptive k-means image segmentation method, and then query images posed by the user are transformed into corresponding positive and negative bags and a EM-DD(expectation maximization diverse density) algorithm is employed for image retrieval and relevance feedback. Finally, it makes the users get satisfying result.