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Improving the accuracy of old and young face detection in the template matching method with Fuzzy Associative Memory(FAM)

机译:用模糊关联记忆(FAM)在模板匹配方法中提高旧脸检测的准确性

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Every human has a face pattern and certain characteristics even though identical twins,but the human face pattern still has its own distinctiveness as well as old face patterns and young face patterns even though the human face pattern is very diverse but for young and old face patterns will be a difference between one face and the other face.Face detection(face detection)is one of the initial stages that very important in face recognition that is used in biometric identification.Face detection can also be used to search or index face data from images or videos that contain faces of various sizes,positions,and backgrounds.Face detection(face detection)automatically with the help of a computer is a problem that is not easy because the human face has a high level of variability both intra-personal and extra-personal variability.This study shows that systems with template matching methods combined with FAM can successfully detect differences in human faces,80% accuracy,10% better by using ordinary template matching.
机译:每个人都有一个面貌模式和某些特征,即使是相同的双胞胎,而且人类脸部模式仍然有自己的独特性以及旧的面孔模式和年轻的面部图案,即使人类的脸部图案是非常多样化的,而且对于年轻人和旧的面孔模式将是一个面部和另一个面部之间的差异。面积检测(面部检测)是在生物识别识别中使用的面部识别中非常重要的初始阶段之一。面积检测也可用于搜索或索引面部数据包含各种尺寸,位置和背景的面孔的图像或视频。在计算机的帮助下自动检测(面部检测)是一个不容易的问题,因为人类脸部具有高水平的变异性,既有个人和个人此研究表明,具有模板匹配方法的系统与FAM相结合,可以成功地检测人类面的差异,80%的精度,更好地使用10%普通模板匹配。

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