A Novel and Fast Method for Content-Based Image Retrieval via Stack-Triangles Geometrics Histogram

Abstract:

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In this paper, a novel method is proposed for solving an open problem of shape matching in content-based image retrieval. Our method regards the stack-triangles geometrics histogram to be the feature of an image, the correlation of two images was decided by the compare result of their stack-triangles geometrics histograms. First of all, these methods extract the key contour fragments of an image, so that a shape can be presented as many key contour fragments in this way. In addition, we derivation stack triangles of a shape by the key contour fragments we get it before. Then, we can get the stack-triangles geometrics histogram of the image and calculate the correlation of two images use their stack-triangles geometrics histogram. Finally, experiment results show that our new method is a very fast method and can get more robustness than existing methods and achieve a good effect in the standard shape databases MPEG-7.

Info:

Periodical:

Advanced Materials Research (Volumes 341-342)

Edited by:

Liu Guiping

Pages:

785-789

DOI:

10.4028/www.scientific.net/AMR.341-342.785

Citation:

Y. F. Chen et al., "A Novel and Fast Method for Content-Based Image Retrieval via Stack-Triangles Geometrics Histogram", Advanced Materials Research, Vols. 341-342, pp. 785-789, 2012

Online since:

September 2011

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Price:

$35.00

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