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Face Recognition Algorithm Based on Multi-resolution and Classification

机译:基于多分辨率和分类的人脸识别算法

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With the development of computer and internet, how to recognize face images rapidly has become the research focus in recent years. Therefore, face recognition technology develops rapidly, and is widely applied to national counterterrorism, information security and access control. But the researchers find that face recognition only can achieve satisfactory effect under the constraint conditions. The paper proposes face recognition algorithm based on multi-resolution analysis and classification. The algorithm firstly uses wavelet transform for multi-scale wavelet decomposition on training sample, and uses the correlation coefficient between wavelet coefficients with the maximum variance as the classification distance to classify the samples and determine the central image of the images. Face recognition algorithm based on multi-resolution analysis and classification extracts some wavelet coefficients of the images, which not only achieves the purpose of dimension reduction and reduces calculated amount, but also effectively improves the speed of face recognition. The simulation experiment proves that the algorithm proposed in the paper is effective.
机译:随着计算机和互联网的发展,如何迅速识别面部图像已成为近年来的研究重点。因此,人脸识别技术迅速发展,广泛应用于国家反抗,信息安全和访问控制。但研究人员发现,面部识别只能在约束条件下实现令人满意的效果。本文提出了基于多分辨率分析和分类的人脸识别算法。该算法首先在训练样本上使用针对多尺度小波分解的小波变换,并使用小波系数之间的相关系数作为分类距离来分类样本并确定图像的中心图像。基于多分辨率分析和分类的人脸识别算法提取一些图像的小波系数,其不仅实现了尺寸减小的目的并降低了计算量,而且有效地提高了面部识别的速度。仿真实验证明了本文提出的算法是有效的。

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