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Feature Extraction Using Histogram of Oriented Gradient and Hu Invariant Moment for Face Recognition

机译:基于方向直方图和Hu不变矩的特征提取用于人脸识别

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Face recognition was one of many popular fields in Image Processing and Computer Vision. Face recognition had many problems like the pose variation, Illumination, Image Quality, etc. Many methods were developed to find the solution to this problem. Some method uses Approach that uses the whole face as features, while other method uses Features-Based Approach that uses Local Feature like Eyes, Nose, and Mouth as features. The proposed method to combine two methods: HOG and Hu Invariant moment. Two methods as feature extraction has been implemented with tested on 3 database: Markus's, ORL/AT&T and our database. This database was tested with three scenarios testing. Finally, the proposed method result on Recognition Rate average is 79.82 %, then the best Recognition Rate result is 97.22 %.
机译:人脸识别是图像处理和计算机视觉中许多受欢迎的领域之一。人脸识别存在许多问题,例如姿势变化,照明,图像质量等。开发了许多方法来找到解决此问题的方法。某些方法使用将整个脸部作为特征的方法,而其他方法则使用将诸如眼睛,鼻子和嘴巴等局部特征作为特征的基于特征的方法。所提出的方法结合了两种方法:HOG和Hu不变矩。在3个数据库上测试了两种作为特征提取的方法:Markus,ORL / AT&T和我们的数据库。该数据库已通过三种方案测试进行了测试。最后,所提方法的识别率平均值为79.82%,最佳识别率结果为97.22%。

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