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A template extraction approach for image recognition

机译:用于图像识别的模板提取方法

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摘要

A robust approach for extracting template from images with relatively poor quality is presented in this paper. The approach combines fast Fourier transformation algorithm and weighted normalized cross correlation algorithm to deal with images taken under weak template. Basically, it consists of three steps: 1) searching candidate template from the target image using prefabricated template, and 2) determining the count of template matching area and adjusting the candidate template by using neighborhood growth method, and 3) evaluating the optimal template among the candidate templates. A set of experiments has been performed and the results shows that the proposed approach can obtain templates accurately and robustly.
机译:本文提出了一种从质量相对较差的图像中提取模板的可靠方法。该方法结合了快速傅立叶变换算法和加权归一化互相关算法来处理弱模板下拍摄的图像。基本上,它包括三个步骤:1)使用预制模板从目标图像中搜索候选模板; 2)确定模板匹配区域的数量,并使用邻域增长方法调整候选模板; 3)评估其中的最佳模板候选模板。已经进行了一组实验,结果表明所提出的方法可以准确,可靠地获得模板。

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