Abstract
We present an on-line query mechanism for shape-based similarity retrieval of image databases. It successively boosts salient common features among query samples, in which weak classifiers are tuned and selected to contribute to a final strong classifier. The similarity between two shape samples was measured in statistic space of features, through which relative instead of absolute similarity was targeted for visual information retrieval. Experiments of query by the boosted features on thirty thousand trademark images showed that the retrieved results meet visual similarity of shape very well. Only 5 – 7 boosted features out of 100 or more were enough to represent subjective recognition on shape similarity.
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© 2001 Springer-Verlag Berlin Heidelberg
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Chen, JJ., Liul, CY., Huang, YS., Hsieh, JW. (2001). Similarity Retrieval in Image Databases by Boosted Common Shape Features Among Query Images. In: Shum, HY., Liao, M., Chang, SF. (eds) Advances in Multimedia Information Processing — PCM 2001. PCM 2001. Lecture Notes in Computer Science, vol 2195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45453-5_37
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DOI: https://doi.org/10.1007/3-540-45453-5_37
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