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ROI Extraction of Palmprint Images Using Modified Harris Corner Point Detection Algorithm

机译:改进的Harris角点检测算法提取掌纹图像的ROI

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摘要

A new extraction method of palmprint images' region of interesting (ROI) by using a modified Harris corner detection algorithm is discussed in this paper. This method can independently select the corner detection region by using mouse and doesn't need to detect the whole palmprint image. So, the calculation complexity is reduced hardly. At the same time, this method can ensure the uniqueness of detected corners and improve the location accuracy of palmprints. In test, the database of CASIA is used. Compared with the traditional Harris corner detection algorithm, experimental results show that our method can more efficiently and quickly locate palmprint images' ROI, and can efficiently enhance the edge and detail of palmprint images simultaneity.
机译:本文提出了一种改进的Harris角点检测算法,提取掌纹图像的感兴趣区域(ROI)。该方法可以通过鼠标独立选择角点检测区域,不需要检测整个掌纹图像。因此,几乎不降低计算复杂度。同时,该方法可以保证检测到的角点的唯一性,提高掌纹的定位精度。在测试中,使用了CASIA数据库。实验结果表明,与传统的Harris角点检测算法相比,该方法可以更快,更有效地定位掌纹图像的ROI,并可以有效地提高掌纹图像的边缘和细节的同时性。

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