光学技术, 2019, 45 (2): 224, 网络出版: 2019-04-28
危化品仓储激光扫描差值去噪算法的研究
Study on chemical storage stacking laser scanning D-value denoising algorithm
激光测距 点云 差值去噪 危化品仓储 laser distance measuring point cloud D-value denoising storage of dangerous chemicals
摘要
为了实现对危化品仓储堆垛安全距离的实时监测和预警, 采用由激光测距、旋转云台、编码器等组成的激光扫描监控阵列对垛距进行安全监测。针对激光测距扫描点云数据中异常噪声的问题, 采用差值去噪算法。该算法是将扫描得到的激光测距数据点按角度值进行从小到大排序后, 相邻两点的距离值依次取差值, 然后对距离差值与预设阈值进行比较, 滤掉噪点数据。针对几种不同尺寸和形状的障碍物进行了实验研究, 结果表明差值去噪方差值明显小于加权二乘、Savitzky-Golay等拟合算法, 该算法不仅能有效去除扫描点云数据中的异常噪声, 同时较另外两个算法, 数据完整性和可靠性更高。
Abstract
In order to realize the real-time monitoring and warning of the safe distance of hazardous chemical storage stacking, the laser scanning monitoring array composed of laser ranging, rotating cradle head and encoder is used to monitor the safe distance of the stacking.Aiming at the problem of abnormal noise in laser ranging scanning point cloud data, the difference denoising algorithm is adopted.The algorithm is to scan the laser ranging data points from small to large sorted according to angle value is the distance between two values in turn take difference.Then the distance difference compared with the preset threshold filter out noise data.Aimed at several different size and shape of obstacles has carried on the experimental study.The results indicate that the difference to the noise variance value is less than obvious weighted squares,a Savitzky-Golay fitting method.The proposed algorithm not only can effectively eliminate the abnormal noise in the scanning point cloud data at the same time than the other two algorithms,data integrity and higher reliability.
刘学君, 魏宇晨, 李京, 袁碧贤, 卢浩, 戴波, 李翠清. 危化品仓储激光扫描差值去噪算法的研究[J]. 光学技术, 2019, 45(2): 224. LIU Xuejun, WEI Yuchen, LI Jing, YUAN Bixian, LU Hao, DAI Bo, LI Cuiqing. Study on chemical storage stacking laser scanning D-value denoising algorithm[J]. Optical Technique, 2019, 45(2): 224.