Image Alignment Using Pyramid Structure with Harris Corner Detection

Chin-Sheng Chen, S. Tsai, Kang-Yi Peng, Chorng-Tyan Lin, Chih-Chin Wen
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引用次数: 1

Abstract

A corner-based image alignment algorithm based on the procedures of corner-based template matching is presented in this study. This algorithm consists of two stages: training and matching. In the matching phase, the corners are obtained using Harris corner detection algorithm. These corners are then used to build the pyramid images. In the matching phase, the corners are obtained using the same corner detection algorithm. The similarity measure is then determined by the differences of gradient vector between the corners obtained in the template image and the inspection image, respectively. Furthermore, it further applied the refined function to evaluate the geometric relationship between the template and the inspection images. Results show that the corner-based template matching outperforms the original edge-based template matching in efficiency, and both of them are robust against lighting changes.
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使用金字塔结构与哈里斯角检测图像对齐
提出了一种基于角点模板匹配的角点图像对齐算法。该算法包括训练和匹配两个阶段。在匹配阶段,采用Harris角点检测算法获取角点。然后用这些角来构建金字塔图像。在匹配阶段,使用相同的角点检测算法获得角点。然后根据模板图像和检测图像中得到的角点梯度向量的差异确定相似性度量。在此基础上,进一步应用改进函数对模板与检测图像之间的几何关系进行评价。结果表明,基于角的模板匹配在效率上优于原始的基于边缘的模板匹配,并且对光照变化具有较强的鲁棒性。
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