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Vol. 165, Issue 2, February 2014, pp. 137-141




A Novel Real-Time Feature Matching Scheme

Ying Liu, * Hongbo Bi, Mengmeng Wu, Wufeng Yue, Panpan Zhao

North East Petroleum University, Daqing, 163318, China
* Tel.: 086-0459-6503272, fax: 086-0459-6503160

* E-mail: bhbdq@126.com


Received: 14 November 2013 /Accepted: 28 January 2014 /Published: 28 February 2014

Digital Sensors and Sensor Sysstems


Abstract: Affine Scale Invariant Feature Transform (ASIFT) can obtain fully affine invariance, however, its time cost reaches about twice that in Scale Invariant Feature Transform (SIFT). We propose an improved ASIFT algorithm based on feature points in scale space for real-time application. In order to detect the affine invariant feature point, we establish a second-order difference of Gaussian (DOG) pyramid and replace the extreme detection in the DOG pyramid by zero detection in the proposed second-order DOG pyramid, which decreases the complexity of the scheme. Experimental results show that the proposed method has a big progress in the real-time performance compared to the traditional one, while preserving the fully affine invariance and precision.


Keywords: Scale space, Affine invariance, Scale invariant feature transform, Difference of Gaussian.


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