基于特征融合的二代身份证人脸验证系统

Feature fusion-based face verification on second generation identity card

二代身份证人脸验证是指判断二代身份证图片和身份证使用者当前头像是否为同一人.由于二代身份证图片分辨率较低,与现场采集图像的清晰度、人脸内部变化、外在环境等差异较大,传统的人脸识别方法在解决二代身份人脸验证问题时识别率较低.针对上述问题,提出一种基于特征融合的二代身份证人脸验证系统.该系统包括图像采集、预处理、特征提取、特征比对及结果判断五个部分.首先采集二代身份证图片和摄像头照片并进行图像预处理,分别提取二代证照片和摄像头照片的全局特征和局部特征,全局特征采用PCA和LDA方法,局部特征采用直方图方向二进制码(HDBC)方法;然后对全局特征和局部特征在公共特征空间内计算相似性,得到全局特征和局部特征的相似性,最终根据给定的阈值判断二代身份证持有人是否为本人;最后在大量真实的二代证数据集上进行测试验证,结果表明,该方法相比于传统的单特征提取算法,识别率显著提高.

The second-generation ID card face verification refers to judging whether the photo on the second-generation ID card matches its user Due to its low resolution,the second-generation ID card photo differs greatly from the photo taken on the spot in terms of clarity,facial changes,and the external environment,resulting in the low recognition rate of the conventional face recognition method.To solve this problem,t a second-generation ID card facial verification system based on feature fusion is proposed.The system consists of five parts:image acquisition,preprocessing,feature extraction,feature comparison,and result judgment.First,the second-generation ID card image and camera photo are collected and image preprocessing is performed.The global and local features of the second-generation card photo and camera photo are then extracted separately.Global features are extracted by PCA and LDA methods,and local features are extracted by the histogram directional binary code(HDBC)method.Then,the global and local features are calculated in the common feature space,and the similarity between the global features local features is obtained.Finally,the user of the second-generation ID card is tested based on the given threshold.Experiments have been performed on a large number of real second-generation ID card datasets.Compared with the traditional single feature extraction algorithms,the recognition rate of the proposed method is significantly improved.