Feature fusion-based face verification on second generation identity card

doi:10.3969/j.issn.0253-2778.2019.10.008

Abstract

Abstract: 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.

Key words: face verification, second-generation ID card, global feature, local feature, feature matching

CLC Number:

TP391

WANG Zhong, CHEN Enhong, LIU Guiquan. Feature fusion-based face verification on second generation identity card[J]. Journal of University of Science and Technology of China, 2019, 49(10): 828-834.

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