北京交通大学学报2018，Vol.42Issue(2)：22-30,9.DOI:10.11860/j.issn.1673-0291.2018.02.004
双目视觉的原木径级快速检测算法
Rapid detection algorithms for log diameter classes based on binocular vision
摘要
Abstract
Aimed at the key problem that automatic detection of log piles diameter classes,by the binocular stereo vision and image segmentation principle,3D information of log-end is determined rapidly.According to the histogram feature of log-end,a region labeling method based on the maximum entropy threshold segmentation is presented,which sets the dynamic threshold to achieve the accurate segmentation of the log-end area and background.Meanwhile,with the help of the ORB feature point detection method,combined the epipolar geometry theory with stereo matching,the 3D coordinates are obtained rapidly.Otherwise taking the log piles as the detection object,the least squares principle is fitted to get the best fitting ellipse and log diameter class parameters of major axis and minor axis.Experiment shows that the proposed algorithms can detect the log diameter classes in 10 s,and the measurement error is in the 2 mm.关键词
模式识别/原木径级/双目视觉/立体匹配/椭圆拟合Key words
pattern recognition/log diameter class/binocular vision/image identification/ellipse fitting分类
信息技术与安全科学引用本文复制引用
陈广华,张强,陈梅倩,李建伟,尹怀永..双目视觉的原木径级快速检测算法[J].北京交通大学学报,2018,42(2):22-30,9.基金项目
国家自然科学基金(51376017)National Natural Science Foundation of China (51376017) （51376017）
