一种基于激光传感器的自适应直线提取算法  

Self-adaption segmentation algorithm for line extraction based on laser sensor

作　　者：徐君[1] 张国良[1] 王俊龙[1] 

机构地区：[1]第二炮兵工程学院301教研室,西安710025

出　　处：《计算机工程与应用》2013年第2期43-47,共5页Computer Engineering and Applications

摘　　要：针对Split-and-Merge直线提取算法对参数敏感和运算效率低的问题,提出一种基于该算法的自适应直线提取方法,根据自适应阈值对激光数据进行邻近点簇分割,基于Prototype-based fuzzy clustering算法对邻近点簇进行线段分割,利用最小二乘拟合直线参数。实验结果证明,该方法显著提高了线段分割的鲁棒性和线段提取的精度,以及算法的运算效率。Aiming to the problem that the Split-and-Merge segmentation algorithm is very sensitive to changes on some parameters and inefficiency, this paper proposes a self-adaption line extraction algorithm based on it. This algorithm divides the laser sensor data into many near point aggregates by a self-adaption threshold, after that it segments the near point aggregates to many lines with Prototype-based fuzzy clustering algorithm. It estimates lines parameters according to the least square criterion. Experimental results demonstrate that all of robustness to line segmentation, precision to line extraction and efficiency to the algorithm are improved significantly.

关 键 词：直线提取 SPLIT and—Merge 特征描述 激光传感器 最小二乘法 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]