Quad-tree segmentation for texture-based image query
MULTIMEDIA '94 Proceedings of the second ACM international conference on Multimedia
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONTEXT: A Technique for Image Retrieval Integrating CONtour and TEXTure Information
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
IEEE Transactions on Multimedia
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In this paper, we present a ROI (Region-Of-Interest)-based medical image retrieval system that is considering combination of feature descriptors and initial weights for similarity matching. For semantic ROI segmentation, we create attention window (AW) to remove the meaningless regions included in the image such as background and propose a quad-tree based ROI segmentation method. In addition, in order to improve the retrieval performance and consider human perception, initial weights for feature distances are also proposed. From, several experiments, we demonstrate that the ROI-based method having different initial weights shows the better performance than previous related methods.