液晶与显示2018，Vol.33Issue(12)：1033-1039,7.DOI:10.3788/YJYXS20183312.1033
基于特征域聚类下Radon变换的火车票图像方向检测算法研究
Direction detection algorithm of train ticket images based on Radon transform with feature area clustering
摘要
Abstract
With the development of transportation service industry in China, automatic identification of railway ticket information has become more important to improve the efficiency of railway service.In order to solve the problem of inconsistency in train ticket direction acquisition in ticket surface information recognition system, a direction detection algorithm is proposed in this paper which is based on Radon transform with feature area clustering.Firstly, the algorithm classifies train ticket images by K-means clustering, eliminates the interference of complex background and extracts the railway ticket information area.Then, the image direction feature area which can reflect the train ticket position information is preserved through digital morphology closed operation combined with image block operation.Finally, the tilted angle of train ticket is detected by the improved Radon transform.The experimental results show that the correction accuracy of the algorithm is 97.8％, and the correction time is 16.79 s.By the algorithm, it can eliminate the interference of the image complex background and neighborhood pixels of direction feature area to the direction detection, and detect the direction of train ticket image in any direction with full angles, which are of high practical value.关键词
火车票图像/方向检测/图像方向特征区域/k均值聚类/Radon变换Key words
train ticket image/direction detection/image direction feature area/K-means clustering/Radon transform分类
信息技术与安全科学引用本文复制引用
许亚杰,韦海成,肖明霞..基于特征域聚类下Radon变换的火车票图像方向检测算法研究[J].液晶与显示,2018,33(12):1033-1039,7.基金项目
宁夏自然科学基金项目(No.NZ17104) （No.NZ17104）
宁夏双一流学科与科研项目(电子科学与技术No.NXYLXK2017A07) （电子科学与技术No.NXYLXK2017A07）
国家自然科学基金项目(No.61461001,No.61861001) （No.61461001,No.61861001）
北方民族大学智能感知及控制校级重点实验室 （）
北方民族大学研究生创新项目(No.YCX18071) （No.YCX18071）
