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    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/78886


    題名: Integrating SIFT and Harris corner detector for definite keypoint extraction for image matching
    作者: Chen, Chengyi;Chio, Shih Hong
    邱式鴻
    貢獻者: 地政學系
    關鍵詞: Feature point extraction;Harris corner detector;Keypoints;Scale and rotation;Scale invariant feature transforms;SIFT;Algorithms;Feature extraction;Photogrammetry;Remote sensing;Image matching
    日期: 2011
    上傳時間: 2015-10-08 17:36:31 (UTC+8)
    摘要: Feature point extraction automatically instead of manually is important and can improve the efficiency for photogrammetric tasks. Scale invariant feature transform (SIFT) is an important algorithm developed by Lowe (2004) to extract keypoints with invariance on scale and rotation for image matching and registration. Not all these kinds of keypoints do correspond to the definite position of object points in real world, therefore not all of them are suitable for precise localization in photogrammetric task. The definite keypoints can be used for image matching and precise location of object points. For photogrammetric applications, Harris corner detector is often employed to detect definite and precise keypoints, but those kinds of keypoints do not have the characteristics of invariance on scale and rotation. Therefore, this study will integrate SIFT and Harris corner detector to extract the precise and definite keypoints for image matching in order to determine the precise location of object points. Meanwhile, the efficiency of image matching from the extracted keypoints will be investigated in this study.
    關聯: 32nd Asian Conference on Remote Sensing 2011, ACRS 2011
    資料類型: conference
    顯示於類別:[地政學系] 會議論文

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