Paper
5 November 2020 License plate photo recognition technology based on micro-nano filter
Ziling Chen, Jianping Zeng, Guangyi Xiao, Xiaoli Xie, Jingyue Fang
Author Affiliations +
Proceedings Volume 11567, AOPC 2020: Optical Sensing and Imaging Technology; 1156735 (2020) https://doi.org/10.1117/12.2580091
Event: Applied Optics and Photonics China (AOPC 2020), 2020, Beijing, China
Abstract
In the process of the license plate photo recognition process, light and external environment are important factors for the clarity of the photo result. We first add a 400nm filter in front of the camera to carry out the experiment, take pictures with ultraviolet rays light and without ultraviolet rays light source irradiation, then add a 390nm filter in front of the camera to perform the same experiment for comparison. Perform comparative analysis and image processing on the experimental shooting results. First, it can be seen from the comparison of the shooting results that the clarity and recognition of the image under the action of the 400nm filter are significantly improved compared with that of the 390nm filter. Second, the image processing is used to analyze the results, which can effectively identify the license plate information. Finally, the license plate is irradiated with micro-nano filter and ultraviolet light source instead of the monitor fill light, so the strong light stimulation to the driver's eyes is avoided, thereby alleviating the short-term ‘light blindness’ phenomenon of the human eyes and reducing the hidden safety hazards when driving.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ziling Chen, Jianping Zeng, Guangyi Xiao, Xiaoli Xie, and Jingyue Fang "License plate photo recognition technology based on micro-nano filter", Proc. SPIE 11567, AOPC 2020: Optical Sensing and Imaging Technology, 1156735 (5 November 2020); https://doi.org/10.1117/12.2580091
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KEYWORDS
Optical filters

Light sources

Image filtering

Image processing

Image segmentation

Light

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