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High-speed template matching algorithm using contour information

机译:利用轮廓信息的高速模板匹配算法

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摘要

Abstract: We propose a new high speed template matching algorithm named edge point template matching (EPTM), which can match one gray image to another closely similar image and detect small differences between them. This method uses location, strength, and direction of contours in the template image. They are stored in a one-dimensional array. This reduced template makes the computational cost lower than previous methods which have a two- dimensional template. Generally, this kind of template reduction causes a mismatch when the image is disturbed. Contour dilation of the target image improves this situation. By applying the coarse-fine algorithm and the sequential similarity detection algorithm, our method is approximately 300 times faster than the well known cross-correlation technique. A simple hardware architecture is enough to implement the algorithm, and it is possible to execute matching a 400 $MUL 400 template on a 512 $MUL 512 target image within 200 msec.!6
机译:摘要:我们提出了一种新的高速模板匹配算法,称为边缘点模板匹配(EPTM),该算法可以将一个灰度图像匹配到另一个紧密相似的图像,并检测它们之间的细微差异。此方法使用模板图像中轮廓的位置,强度和方向。它们存储在一维数组中。该减少的模板使得计算成本低于具有二维模板的先前方法。通常,当图像受到干扰时,这种模板缩小会导致不匹配。目标图像的轮廓扩张可以改善这种情况。通过应用粗精细算法和顺序相似性检测算法,我们的方法比众所周知的互相关技术快约300倍。一个简单的硬件架构足以实现该算法,并且有可能在200毫秒内在512 $ MUL 512目标图像上执行匹配400 $ MUL 400模板的工作!6

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