Mining Visual Data

Abstract

The Internet offers to its users an ever-increasing number of information. Among those, the multimodal data (images, text, video, sound) are widely requested by users, and there is a strong need for effective ways to process and to manage it, respectively. Most of existed algorithms/frameworks are doing only images annotations and the search is doing by these annotations, or combined with some clustering results, but they do not allow a rapid browse of these images. In this paper, an image retrieval system is presented, including detailed descriptions of used lwo-SOM approach and a novel interactive learning using user information/response. Also, we show the use of unsupervised learning for images, we do not dispose of the labels, and we will not take into account the corresponding text for the images. The used DataSet contains 17812 images extracted from wikipedia pages, each of which is described by it colors and texture.