OPT OpenIR  > 飞行器光学成像与测量技术研究室
Image Enhancement Technology in Pavement Disease Detection System
Li, Xuefeng1; Zhou, Zuofeng2; Wu, Qingquan2
2022
会议名称2nd IEEE International Conference on Electronic Technology, Communication and Information, ICETCI 2022
会议录名称2022 IEEE 2nd International Conference on Electronic Technology, Communication and Information, ICETCI 2022
页码547-549
会议日期2022-05-27
会议地点Changchun, China
出版者Institute of Electrical and Electronics Engineers Inc.
产权排序1
摘要

Efficient pavement bad location detection and repair is essential to prolong the use time of roads. However, traditional manual detection methods are extremely inefficient and can no longer meet the requirements of inspecting a large number of roads. When using deep learning technology for road disease detection, it is found that low-illuminance images will affect the detection accuracy due to low contrast. Therefore, before training and testing the deep learning model, the original image needs to be preprocessed to improve the image quality. First, bilateral filtering is used instead of Gaussian filtering to estimate the illuminance of the original image; Then the reflection component is get according to the principle of Retinex algorithm, and the reflection image is quantized; Finally, the image is subjected to illumination compensation. The results of comparative experiments display that the ours algorithm can retain the characteristic details of road diseases and eliminate the unevenness of the image brightness distribution while improving the contrast of the road image. © 2022 IEEE.

关键词pavement diease retinex image enhancement
作者部门飞行器光学成像与测量技术研究室
DOI10.1109/ICETCI55101.2022.9832258
收录类别EI
ISBN号9781728181158
语种英语
EI入藏号20223312571189
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/96123
专题飞行器光学成像与测量技术研究室
通讯作者Zhou, Zuofeng
作者单位1.Xi'an Institute of Optics and Precision Mechanics, Cas, University of Chinese Academy of Sciences, Beijing, China;
2.Xi'an Institute of Optics and Precision Mechanics, Cas, Industrial Development Co., Ltd, Xi'an, China
推荐引用方式
GB/T 7714
Li, Xuefeng,Zhou, Zuofeng,Wu, Qingquan. Image Enhancement Technology in Pavement Disease Detection System[C]:Institute of Electrical and Electronics Engineers Inc.,2022:547-549.
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