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机构地区:[1]昆明理工大学,昆明650500
出 处:《微处理机》2012年第1期67-70,共4页Microprocessors
基 金:教育部"春晖计划"资助项目(KKQA200603002)
摘 要:根据夜间光照不充足的情况提出了一种有效的车流量统计算法。首先应用阈值化,分离出前景和背景,通过形态学腐蚀去除一些孤立的点以及特小区域,寻找联通区域丢弃小于设定范围的较小区域,利用形态学膨胀连接被分离的车头灯投射的光束;其次计算并判断连通区域的面积和范围,准确地提取出车灯对并且将其配对;最后通过比较前后两帧车头灯对的位置和面积对其进行跟踪,统计其车流量。实验表明,该算法复杂度较低,在良好环境下检测率可以达到97%以上。An efficient algorithm was presented for the statistics of traffic flows including that illumi- nation was not sufficient at night. Firstly, In order to separate the foreground from background, the original video sequences had been thresholded, and by using morphological erosion to eliminate some isolated noises and smaller regions, these regions whose ranges are smaller than the one enacted were discarded by looking for connective regions, and the beams which were projected by headlamps and detached ,were connected by the morphological expansion. Secondly, calculating and judging the areas and ranges of connective regions to extract accurately the headlights. Finally, comparing the headlights' areas and position of two adjacent frames to match and track, then calculate traffic flows. Experiment results indicate that this algorithm is low about computation, and its detection ratio reaches above 97% in fine condition.
分 类 号:TP391.4[自动化与计算机技术—计算机应用技术]
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