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Binary image matching using scale invariant feature and hough transforms

机译:使用Scale Invariant功能和Hough变换匹配二进制图像匹配

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Scale Invariant Feature Transform (SIFT) is used for local features description of images. The proposed technique employs SIFT in order to match binary images. While the employment of SIFT descriptors on binary image databases could be possible, its power is rather limited. The novelty of the proposed algorithm is make use of SIFT for binary image matching by taking the power of Hough Transform (HT) in line detection. HT can be used on any line orientation. Thus, HT investigates lines as criteria for binary image similarity beside SIFT features for local and corner descriptions. The evaluation is achieved and experimental highlights the superiority of this approach for binary images which contains straight lines.
机译:缩放不变功能变换(SIFT)用于本地特征图像的描述。所提出的技术采用SIFT以匹配二进制图像。虽然在二进制图像数据库上的使用描述符的工作可能是可能的,但其功率相当有限。通过在线检测中掌握Hough变换(HT)的功率,提出了该算法的新颖性是利用二进制图像匹配的筛选。 HT可用于任何线路方向。因此,HT调查线条作为局部和角色描述的筛选特征旁边的二进制图像相似性的标准。实现评估且实验强调了包含直线的二元图像方法的优势。

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