【摘要】 针对当前人脸识别受噪声等干扰导致识别效果不佳的问题,提出一种人脸识别方法,利用具有抗光照不变性的近红外人脸图像进行人脸识别算法分析。为增强算法在图像抗噪声方面的性能,通过均匀局部二元模式提取人脸图像的特征;为避免细节纹理的缺失,采用对人脸图像分块处理的方法建立特征;通过引入稀疏分类算法,进行人脸识别。实验结果表明,该人脸识别算法相比传统方法具有良好的稳健性与识别率,达到了提高人脸识别算法性能的目的。更多还原

【Abstract】 In view of the poor results of the current face recognition caused by noise and other problems,a face recognition method was presented.The near-infrared face image with anti-illumination-invariant for the research of face recognition algorithm was used.To enhance the performance of anti-noise,the uniform local binary pattern was utilized to extract face features.The face image was blocked to avoid the detail texture missing and construct face features.A method of sparse representation for face classification was used.Experimental results demonstrate that the proposed method is robust with better recognition compared with the traditional method.The face recognition algorithm can benefit a lot from the proposed approach.更多还原