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作 者:刘珂琪 董绵绵[1] 王鹏[1] 李晓艳[1] 吕志刚[1] 郭宝亿 Liu Keqi;Dong Mianmian;Wang Peng;Li Xiaoyan;Lyu Zhigang;Guo Baoyi(School of Electronic and Information Engineering,Xi'an Technological University,Xi'an 710000,China;Industrial Center,Xi'an Technological University,Xi'an 710000,China)
机构地区:[1]西安工业大学电子信息工程学院,西安710000 [2]西安工业大学工业中心,西安710000
出 处:《电子测量技术》2022年第7期137-145,共9页Electronic Measurement Technology
基 金:国家自然基金(62171360);陕西省科技厅项目(2019GY-058);西安市科技计划项目(2020KJRC0037);西安市未央区科技计划项目(201923)资助。
摘 要:针对现有传统算法在光照不均匀、背景复杂的情况下对交通信号灯的识别精度低、漏检率高的问题,本文提出了一种基于图像增强的交通信号灯识别方法。首先采用改进的迭代法对原图像进行处理;接着在HSV颜色空间中增强原图像的V通道亮度信息,利用自调节的颜色阈值范围筛选出交通信号灯的颜色候选区域;最后,分别提取原图像经过双处理后获取到的图像轮廓,结合两张图像中的轮廓信息筛选出信息相同的候选区域,并通过计算候选区域的面积、宽高比判断出交通信号灯的区域,从而完成交通信号灯的识别。实验结果表明,在光照不均匀和复杂背景条件下,该算法比现有其他传统算法的识别准确率提升了1.05%,并具有良好的实时性。Aiming at the problems of low accuracy and high missed rate of the existing traditional algorithms in traffic light recognition under the condition of uneven illumination and complex background,this paper proposes a traffic light recognition method based on image enhancement.First,an improved iterative method is used to process the original image.Then,the V-channel brightness information of the original image is enhanced in the HSV color space,and the color candidate regions of traffic lights are screened by self-adjusting color threshold range.Finally,the contour of the original image obtained after dual processing was extracted respectively,and the candidate area with the same information was screened by combining the contour information of the two images,and the area of the traffic signal light was judged by calculating the area and aspect ratio of the candidate area,so as to complete the identification of the traffic lights.Experimental results show that the proposed algorithm can improve the recognition accuracy by 1.05%compared with other traditional algorithms under the condition of uneven illumination and complex background,and has good real-time performance.
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