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Information Technology Journal

Year: 2011 | Volume: 10 | Issue: 11 | Page No.: 2189-2195
DOI: 10.3923/itj.2011.2189.2195
Robust Description Method of SIFT for Features of License Plate Characters
Yang Meng-Ning, LI Xiang-Jun and Zhang Xiao-Hong

Abstract: SIFT is one of descriptor algorithms with the most robustness. However, this extraction algorithm with the scale-invariant image feature point is complex and has the large amount of calculation which can not satisfy the real-time property of license plate character recognition. To solve this problem, this study proposes a simplified SIFT descriptor generating algorithm. Based on the characteristics of the plate character, the geometric center of license plate characters is taken as the feature points and then the main direction is found through PCA algorithm to simplify the process of detecting feature points. Combined with SVM classification algorithm, a new recognition method for license plate characters is proposed. Experimental results show that the simplified SIFT descriptor well maintains the robustness of original SIFT descriptor. In addition, the recognition method for license plate characters makes a good effect on the recognition of slant, fuzzy and partly missing license plate characters.

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How to cite this article
Yang Meng-Ning, LI Xiang-Jun and Zhang Xiao-Hong, 2011. Robust Description Method of SIFT for Features of License Plate Characters. Information Technology Journal, 10: 2189-2195.

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