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An efficient system for recognition of human face in different expressions by some measured features of the face using laplacian operator

机译:使用拉普拉斯算子通过面部的某些测量特征识别不同表情的人脸的有效系统

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摘要

In this paper we present an efficient system for face recognition with high recognition rate. In our proposed method, at first we detect the face from an image, then two main significant edge lines - chin-line and nose-line are determined and next we apply third order polynomial regression on these two lines to get a third order polynomial equation with four coefficients for each line. Here we use Laplacian operator to determine the curve of chin line and nose line. Then we measure distances from the middle point of the nose curve to the chin line horizontally and vertically, the width of the two eyebrows, the width of forehead and the distance from pupil to eyebrow. We also determine two regions - eye-region and nose-region. For each of these regions, we determine the average value of each three basic colors: red, green and blue. We then store the coefficients of the detected edge lines, the average values of the three basic colors and other distances and perform the task of recognition process. The existing face is recognized for which the weighted error is minimum and higher than a predefined threshold value. Experimental results show that our proposed method successfully recognizes face at a very high rate.
机译:在本文中,我们提出了一种具有高识别率的有效人脸识别系统。在我们提出的方法中,首先我们从图像中检测出人脸,然后确定两条主要的显着边缘线-下巴线和鼻子线,然后在这两条线上应用三阶多项式回归以获得三阶多项式方程每行有四个系数。在这里,我们使用拉普拉斯算子来确定下巴线和鼻子线的曲线。然后,我们测量从鼻子弯曲的中点到水平和垂直方向的下巴线之间的距离,两个眉毛的宽度,前额的宽度以及瞳孔到眉毛的距离。我们还确定了两个区域-眼睛区域和鼻子区域。对于这些区域中的每一个,我们确定三种基本颜色的平均值:红色,绿色和蓝色。然后,我们存储检测到的边缘线的系数,三种基本颜色的平均值以及其他距离,并执行识别过程。识别出其加权误差最小且高于预定阈值的现有面部。实验结果表明,我们提出的方法能够以很高的比率成功识别人脸。

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