文章基本信息

标题：Enhanced rotational feature points matching using orientation correction
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作者：Kam Meng Goh ; Syed Abd Rahman Abu-Bakar ; Musa Mohd Mokji 等
期刊名称：ELCVIA: electronic letters on computer vision and image analysis
印刷版ISSN：1577-5097
出版年度：2014
卷号：13
期号：1
页码：68-88
语种：Undetermined
出版社：Centre de Visió per Computador
摘要：In matching between images, several techniques have been developed particularly for estimating orientation assignment in order to make feature points invariant to rotation. However, imperfect estimation of the orientation assignment may lead to feature mismatching and a low number of correctly matched points. Additionally, several possible candidates with high correlation values for one feature in the reference image may lead to matching confusion. In this paper, we propose a post-processing matching technique that will not only increase the number of correctly matched points but also manage to solve the above mentioned two issues. The key idea is to modify feature orientation based on the relative rotational degree between two images, obtained by taking the difference between the major correctly matched points in the first matching cycle. From the analysis, our proposed method shows that the number of detected points correctly matched with the reference image can be increased by up to 50%. In addition, some mismatched points due to similar correlation values in the first matching round can be corrected. Another advantage of the proposed algorithm it that it can be applied to other state-of-the-art orientation assignment techniques.