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A rotation and scale invariance face Recognition Method Based on Complex Network and Image Contour

机译:基于复杂网络和图像轮廓的旋转和尺度不变性人脸识别方法

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The Method based on Image Contour and shape can achieve high identify efficiency with simple process. But the change of the facial expression, light intensity or position of shelters will reduce the recognition effect. To solve these problems, a Face Recognition Method Based on Complex Network and Image Contour is discussed in this paper. The main idea of the approach is to extract the face image contour, model them into graphs and use complex network methodology to extract a feature vector for face recognition. Experiments show that the proposed method could effectively control the scale of the complex network and adapt to the changes in the boundary shape with efficient power of face recognition. The proposed method is also proved to be scale invariant and rotation invariant.
机译:基于图像轮廓和形状的方法可以实现较高的识别效率,并且过程简单。但是面部表情,光线强度或庇护所位置的变化会降低识别效果。为了解决这些问题,本文讨论了一种基于复杂网络和图像轮廓的人脸识别方法。该方法的主要思想是提取面部图像轮廓,将其建模为图形,并使用复杂的网络方法提取特征向量以进行面部识别。实验表明,该方法能够有效地控制复杂网络的规模,并以有效的人脸识别能力适应边界形状的变化。所提出的方法也被证明是尺度不变和旋转不变的。

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