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针对基于图像特征点的配准方法中对应特征对难以准确提取的问题,提出一种基于兴趣
点匹配的图像自动拼接方法。该方法首先利用Harris角检测器提取两幅图像中的兴趣点,并在此基
础上采用比较最大值法提取出对应兴趣点特征对,最后利用这些匹配特征对来实现图像的拼接。实
验结果表明,这种方法能有效地去除伪匹配特征对的干扰,同时降低了误匹配的概率-Feature points for image-based registration method of the corresponding char
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Automatic license plate recognition
(LPR) is one of the techniques that can be used
for the identification of vehicles. The purpose of
this paper is to investigate a suitable way to
recognize the registration plate from an image of
vehicle,
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用Hausdorff距离对两角点集进行配准，得到点集间的仿射变换，从而实现图像的自动配准。此算法以角点作为Hausdorff距离的配准特征，与直接选用边缘来配准的方法相比较，大大减小计算量。-Hausdorff distance on the corners with a point set registration, be affine transformation between sets in order to achieve automatic image registration. T
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用Hausdorff距离对两角点集进行配准，得到点集间的仿射变换，从而实现图像的自动配准。此算法以角点作为Hausdorff距离的配准特征，与直接选用边缘来配准的方法相比较，大大减小计算量。-Hausdorff distance on the corners with a point set registration, be affine transformation between sets in order to achieve automatic image registration. T
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用Hausdorff距离对两角点集进行配准，得到点集间的仿射变换，从而实现图像的自动配准。此算法以角点作为Hausdorff距离的配准特征，与直接选用边缘来配准的方法相比较，大大减小计算量。-Hausdorff distance on the corners with a point set registration, be affine transformation between sets in order to achieve automatic image registration. T
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用Hausdorff距离对两角点集进行配准，得到点集间的仿射变换，从而实现图像的自动配准。此算法以角点作为Hausdorff距离的配准特征，与直接选用边缘来配准的方法相比较，大大减小计算量。-Hausdorff distance on the corners with a point set registration, be affine transformation between sets in order to achieve automatic image registration. T
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用Hausdorff距离对两角点集进行配准，得到点集间的仿射变换，从而实现图像的自动配准。此算法以角点作为Hausdorff距离的配准特征，与直接选用边缘来配准的方法相比较，大大减小计算量。-Hausdorff distance on the corners with a point set registration, be affine transformation between sets in order to achieve automatic image registration. T
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AAA基于多特征的图像自动配准，该算法不仅降低了计算量,而且减少了误配的可能性,并且对灰度差异较大的图像也是适用的。-AAA-based multi-feature image automatic registration, the algorithm not only reduces computation, but also reduce the possibility of error distribution and intensity differences on the larger
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运动视频序列影像的自动配准运动视频序列影像的自动配准-Automatic registration of the automatic registration campaign video image sequences of moving video image sequences
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Automatic quantification of regional left ventricular deformation in volumetric ultrasound data remains challenging. Many methods have been proposed to extract myocardial motion, including techniques using block matching, phase-based correlation, dif
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基于角点和Hu矩不变量的可见光和红外图像自动配准方法-Based corner and Hu moment invariants visible and infrared automatic image registration method
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