Similarity Measurement Based on Trigonometric Function Distance

Abstract

With the research and analysis on similarity measures which are commonly used in cross-media retrieval and content based image retrieval (CBIR), a new method called trigonometric function distance is proposed. This method satisfies metric properties, and is better than Euclidean distance and Minkowski distance in image similarity. To support this new theory, an algorithm for object shape analysis is designed, and experiments based on trigonometric function distance are conducted. Experiments give an encouraging high recognition rate by using the new similarity measurement

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Cite this paper

@article{Li2006SimilarityMB, title={Similarity Measurement Based on Trigonometric Function Distance}, author={Zongmin Li and Kunpeng Hou and Hua Li}, journal={2006 First International Symposium on Pervasive Computing and Applications}, year={2006}, pages={227-231} }