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Face Recognition Based on Polynomial Fuzzy Matching

机译:基于多项式模糊匹配的人脸识别

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The dimensionality of face image is high very much. It has a lot of difficulty in face recognition. In this paper, first, the concepts of polynomial fuzzy matching based on four rulers (two point rulers and two slope rulers) are introduced. It is not practical because all the slopes m{sub}i must be given at the beginning. It is presented that the fuzzy matching for a nonlinear function between input and output can be realized by using three rulers (two point rulers and one slope ruler). The affinity between two memberships can be used for assessment to the linearity of the matched curve. The image is composed of some curves. So the affinity can be used in face image recognition. Before recognition, the nonlinear dimensionality reduction algorithm Isomap is applied in face images. Then the polynomial fuzzy matching based on three rulers algorithm is applied in face recognition. The experiments show that this method is feasible and has good recognition capability
机译:面部图像的维度非常高。它对人脸识别有很多困难。在本文中,首先,引入了基于四个尺子(两个点尺和两个斜率尺)的多项式模糊匹配的概念。它不实用,因为所有斜率m {sub}我必须在开始时给出。介绍,通过使用三个尺子(两个点尺尺和一个斜率尺),可以实现输入和输出之间的非线性功能的模糊匹配。两个会员资格之间的亲和力可用于评估匹配曲线的线性度。图像由一些曲线组成。因此,亲和力可以用于面部图像识别。在识别之前,在面部图像中应用非线性维度降低算法ISOMAP。然后基于三个统治者算法的多项式模糊匹配应用于面部识别。实验表明,该方法是可行的,具有良好的识别能力

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