Image Retrieval via CURE Clustering and SIFT Algorithms

Abstract:

This paper, by using the short CURE clustering algorithm and image SIFT identification method, the establishment of a kind of image semantic clustering fusion model (image text clustering fusion model, referred to as ITCFM). The model is based on component method, the original image components, original text member, image clustering member, text clustering components, clustering fusion member five parts. In ITCM model for image semantic clustering characteristics on the basis of the description and extraction. The experimental results show that ITCM model can effectively to image to describe the high-level semantic, the image retrieval effect is good, and have stable retrieval performance.

• Periodical: Applied Mechanics and Materials (Volumes 303-306)
• Pages: 1573-1576
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.303-306.1573
• Online since: February 2013
• Authors: Xian Tan
• Keywords: CURE Clustering Algorithm, Image Text Clustering Fusion, SIFT Algorithm

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