基于颜色特征聚类的路径标线检测算法  

Path Marking Detection Algorithm Based on Color Feature Clustering

作　　者：孟德欣[1] 王民权[2] 胡国伟[1] 

机构地区：[1]宁波职业技术学院电子信息学院,浙江宁波315800 [2]宁波职业技术学院海天机电学院,浙江宁波315800

出　　处：《计算机工程》2015年第10期236-239,共4页Computer Engineering

基　　金：宁波市2014年自然科学基金资助项目"基于动态辐射的跟踪式光伏板聚光量增益的研究"(2014A610075)

摘　　要：针对视觉导航中路径彩色图像数据量大、维数高,引导标线检测算法耗时较长的问题,提出一种基于颜色特征聚类的快速标线检测算法。在分析常见的标线检测算法特征基础上,建立彩色图像的颜色稀疏矩阵,隔行检测疑似标线的颜色特征点,计算各特征点之间的近邻系数,利用近邻函数法对颜色特征点聚类分析,找出特征点最多的目标类作为标线,按路径结构将特征点连通,并提供路径导航信息。实验结果表明,与传统颜色空间转换和基于霍夫变换的边缘检测算法相比,该算法运算速度较快,能够满足实时性要求。According to the path of color image data volume,high dimension,guide marking detection algorithm and time-consuming problem in visual navigation,a fast marking detection algorithm in path image based on color feature clustering is proposed.Based on the analysis of the common features of marking detection algorithm,it establishes a color sparse matrix on color image,adopts interlacing detection feature point in suspected marking,calculates neighbor coefficient between the each feature point and clusters by using of neighbor function method,finds out the target class with most feature point which is marking,connects the path structure with feature points set,and provides the route navigation information.Experimental results indicate that compared with the conventional color space conversion or edge detection algorithm based on the Hough transform,the speed of this algorithm is fast,and can meet the real-time requirements.

关 键 词：视觉导航 标线检测 最近邻函数法 颜色特征 聚类 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]