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A Proposed Template Image Matching Algorithm for Face Recognition

机译:一种用于人脸识别的模板图像匹配算法

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Automatic matching of people faces is a demanding issue which has recently received increased attention during the recent ages due to its various uses in different applications such as law implementation, security requirements and video indexing. Face images are exposed to a variety of important influences such as illumination variation, difference in looking view, facial expression, occlusion, age difference between compared face images and some individual changes in field settings. Most current face matching algorithms can be classified into two categories; either geometry feature based, or template image based. In this research, a suggested algorithm is developed based on normalized cross correlation algorithm in order to find the similarity measure between verified face images. Normalized correlation is considered one of the methods based on template matching that can be used for finding a presence of a pattern or a feature within an image. A Graphical User Interface (GUI) is prepared to perform all face matching tasks and is used to test face verification. This GUI has been examined by conducting many case studies. The concluded results indicate that the developed algorithm is so robust in face matching and shows good performance
机译:人脸自动匹配是一个迫切的问题,由于其在不同应用中的各种用途(例如法律实施,安全要求和视频索引),近来在近代受到了越来越多的关注。面部图像会受到各种重要影响,例如照明变化,外观差异,面部表情,遮挡,比较的面部图像之间的年龄差异以及野外设置中的某些单独变化。当前大多数人脸匹配算法可以分为两类:基于几何特征或基于模板图像。在这项研究中,提出了一种基于归一化互相关算法的算法,以找到经过验证的人脸图像之间的相似度。归一化相关被认为是基于模板匹配的方法之一,可用于查找图像中图案或特征的存在。准备使用图形用户界面(GUI)来执行所有面部匹配任务,并用于测试面部验证。已通过进行许多案例研究来检查此GUI。结论表明,该算法在人脸匹配方面具有很好的鲁棒性,并且具有良好的性能。

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