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Optical Engineering

Support value of Gaussian-based interest point detector
Author(s): Changcai Yang; Chao Tao; Yuanyuan Fu; Jinwen Tian; Zheng Sheng
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Paper Abstract

We propose a new approach for detecting interest points using the support value of Gaussian function, which uses the support value to represent the salient features of the image. The support values image is computed by convolving the image with the support value filter deduced from the mapped least-squares support vector machines. The multiscale representation is built by successive smoothing of the support values image with a Gaussian kernel. Then, the normalized support value of Gaussian function is used to find the location of interest points and to select the points at which maxima are over scale. We compared our approach to the state of art of approaches using a standard data set. The experimental results show that the proposed approach performs better than other detectors for scenes under scale and blur changes, in terms of the repeatability score. The performance of the proposed approach is also confirmed by the image registrational results. Moreover, an extension of our method to airport recognition is presented.

Paper Details

Date Published: 1 November 2010
PDF: 7 pages
Opt. Eng. 49(11) 117006 doi: 10.1117/1.3517746
Published in: Optical Engineering Volume 49, Issue 11
Show Author Affiliations
Changcai Yang, Huazhong Univ. of Science and Technology (China)
Chao Tao, Huazhong Univ. of Science and Technology (China)
Yuanyuan Fu, China Three Gorges Univ. (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)
Zheng Sheng, China Three Gorges Univ. (China)

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