Visualaization. Image Retrieval System Using Semantic Visualization of Retrieved Images.

Abstract

We have developed a similarity-based image retrieval system that represents retrieved images as a scatter diagram a semantic space. One axis of the space shows the suitability of a keyword assigned to each image. The suitabilities are estimated by linearly transforming the image features of the retrieved data, and the coefficients of the transformation are determined by multiple regression analysis. First, a-user selects images as key images. Then the system retrieves images and calculates the estimated suitablities variance among the retrieved images for each keyword, and presents the user keywords that give the large variances. Next, the user selects a keyword from the given keywords for each axis. Finally, the system displays the retrieved images in the semantic space spanned by the two axes. The system enables the user to apply the center of gravity among the features of the key images to the retrieval. The system thus effectively assists the user in retrieving images by integrating the semantic visualization and the center of gravity retrieval. Testing of the keyword suitability estimation showed that the estimation precision became high by using keywords with the large suitabilites variances.