Title: Study on intelligent traffic search method based on driver facial feature analysis

Authors: Kaidi Chen; Libing Hu; Miaobo Yao; Ledan Qian; Yongchun Zhang

Addresses: Information Technology Center, Wenzhou Medical University, Wenzhou, China ' Training Center, Zhejiang College of Security Technology, Wenzhou, China ' Information Technology Center, Wenzhou University, Wenzhou, China ' The College of Mathematics and Physics, Wenzhou University, Wenzhou, China ' Information Technology Center, Wenzhou University, Wenzhou, China

Abstract: With the rapid development of Internet technology and biometrics technology in China, artificial intelligence has gradually entered into every aspect of people's life. Big data is used to upgrade intelligent traffic search for people, which improves the efficiency and accuracy of people search for people. Intelligent traffic search is a hotspot in the field of biometric identification and plays an important role in social stability. As an important feature, driver's face image can not only provide great help to the detection of illegal vehicles, but also help to carry out the tracing of missing people, so as to maintain social harmony and stability. Therefore, the intelligent traffic search method based on the analysis of driver's facial features has a broad application prospect and research value. This paper investigates the current international top facial recognition algorithm technology level, and proposes a face image illumination invariant feature extraction algorithm and face feature detection ASM algorithm. The experimental results show that the intelligent traffic search method in this paper has a good recognition rate, and the study in this paper also has a certain guiding significance for the application of image processing in the field of intelligent traffic.

Keywords: driver facial features; artificial intelligence; intelligent traffic search; face feature detection.

DOI: 10.1504/IJVICS.2021.115255

International Journal of Vehicle Information and Communication Systems, 2021 Vol.6 No.2, pp.151 - 160

Received: 14 Dec 2019
Accepted: 03 Apr 2020
Published online: 26 May 2021 *

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