作者:李靖宇，程卫月，李子翔，林克正

Authors:LI Jing-yu,CHENG Wei-yue,LI Zi-xiang,LIN Ke-zheng
摘要:摘要:针对低分辨率下小尺度人脸图像缺失有效身份信息导致的识别率低的问题，提出了超分辨率重建的微小人脸识别算法。该算法首先将采集到的低分辨率人脸图像进行超分辨率重建，并采用细节增强的方法，以恢复图像的面部轮廓信息与纹理细节等高频信息，再通过一个改进的密集连接网络做特征提取，进行图像识别。实验结果表明，该方法对于小尺度的人脸图像，在图像识别率上优于其它人脸识别算法，能够有效解决现实环境中微小人脸识别率低的问题。

Abstract:Abstract:Aiming at the problem of low recognition rate caused by the lack of effective identity information in small-scale face images with low resolution, this small face recognition algorithm based on super-resolution reconstruction is proposed. The algorithm first performs super-resolution reconstruction on the collected low-resolution face images, and uses the method of detail enhancement to restore high-frequency information such as facial contour information and texture details of the image, and then uses an improved densely connected network to do feature extraction and image recognition. Experimental results show that this method is aimed at small-scale face images, and is superior to other face recognition algorithms in image recognition rate, and can effectively solve the problem of low recognition rate of small faces in real environments.

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