A study on vehicle bottom safety detection technology based on image feature matching algorithm

Wei Gao; Maoying Li; Chen Chen

doi:10.1117/12.2674545

23 May 2023 A study on vehicle bottom safety detection technology based on image feature matching algorithm

Wei Gao, Maoying Li, Chen Chen

Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 1260429 (2023) https://doi.org/10.1117/12.2674545
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China

Abstract

In recent years, the vehicle safety detection system is a common information management method of vehicle safety detection in various ports and forts. However, it is generally unable to accurately identify by the system, and still needs manual re-inspection. In this paper, the image algorithm is comprehensively utilized after the functions of automatic identification, display storage and foreign object comparison. A large number of image processing, target recognition, depth learning and other technologies are used to realize the accurate identification of abnormal objects. According to the difference between the normal image and the current image in the database, the vehicle bottom image will be detected for the presence of abnormal objects. From the intelligent point of view, the processing level and accuracy of the detection system can be greatly improved to more than 99.1% and the human intervention and foreign object investment can be reduced to the greatest extent. From the perspective of image processing methods, this paper introduces a new safety detection method of vehicle bottom image data identification.

Citation Download Citation

Wei Gao, Maoying Li, and Chen Chen "A study on vehicle bottom safety detection technology based on image feature matching algorithm", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 1260429 (23 May 2023); https://doi.org/10.1117/12.2674545

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KEYWORDS

Databases

Data modeling

Object detection

Feature extraction

Image processing

Detection and tracking algorithms

Target detection

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