Corner-Based Image Alignment using Pyramid Structure with Gradient Vector Similarity

• Main Authors: Kang-Yi Peng, 彭康懿
• Other Authors: Chin-Sheng Chen
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/q4jzjr

碩士 === 國立臺北科技大學 === 自動化科技研究所 === 102 === 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 which is better than intuitive corner detection by experiment. 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 and noise.