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Fuzzy-based recognition of human front faces using the trapezoidal membership function

机译:梯形隶属度函数对人脸的模糊识别

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A fuzzy-based recognition method of human front faces using the trapezoidal membership function is proposed. In the preprocessing step, we extract the face part from the background image by tracking face boundaries under the assumption that the face part is located in the center of a captured image with homogeneous background. Then based on the a priori knowledge of human faces we extract five normalized features. In the recognition step, we propose a fuzzy-based algorithm that employs a trapezoidal membership function that absorbs the variation of feature values of the same person. Computer simulation results with 80 test images of 20 persons show that the proposed method yields higher recognition rate than the conventional ones.
机译:提出了一种基于梯形隶属度函数的模糊人脸识别方法。在预处理步骤中,我们通过跟踪面部边界(假设面部部分位于具有均匀背景的捕获图像的中心)来从背景图像中提取面部部分。然后基于对人脸的先验知识,我们提取了五个归一化特征。在识别步骤中,我们提出了一种基于模糊的算法,该算法采用了梯形隶属度函数,该函数吸收了同一个人的特征值的变化。计算机仿真结果显示,该方法具有20张80张测试图像,与传统方法相比,其识别率更高。

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