基于梯度搜索的模板匹配算法

Xia Jun-bo
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引用次数: 12

摘要

为了提高传统模板匹配方法的跟踪性能,提出了一种新的模板匹配方法。采用圆形模板保证方法的旋转不变性。在极坐标系下,根据原始图像得到微分图像。匹配值由灰度匹配值和差分匹配值组成。差分信息中包含了模板的详细信息,可以提高识别的准确性。采用梯度搜索减少了匹配次数,保证了跟踪系统的实时性。仿真结果表明,本文提出的模板匹配方法比传统方法具有更好的识别和跟踪性能。
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Template matching algorithm based on gradient search
In order to improve the tracking performance of the conventional template matching method, a novel template matching method is proposed. The round template is used to ensure the rotation invariance of the method. The differential image can be got according to the original image in the polar coordinate system. The matching value is composed of the grey matching value and the differential matching value. The differential information contains the detail information of the template, which can enhance the accuracy of recognition. The gradient search is used to reduce the matching times, which can ensure the real time of the tracking system. Simulation results show that the template matching method proposed in this paper has better recognition and tracking performances than the conventional method.
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