卢才武;马玲;阮顺领;

• 1:西安建筑科技大学管理学院

摘要(Abstract)：

针对在露天矿区无人驾驶卡车道路识别中,受矿区道路边缘模糊、阴影与车辙印干扰等因素的影响,往往无法准确检测到实际道路的问题,提出一种基于HSV空间图像处理的矿区道路边缘检测方法。在HSV颜色空间内,利用半阈值小波对图像进行初步去噪,针对矿区道路边界模糊、边缘退化等问题,提出一种基于融合策略的道路图像增强分割处理算法,可以有效地突出道路边缘,最后利用Canny算子实现对矿区非结构化道路边缘检测。实验结果表明,该方法的检测准确率可达到90.0%以上,能有效识别复杂背景下矿区非结构化道路边缘。

关键词(KeyWords)： HSV空间;非结构化道路检测;多尺度Retinex算法;局部对比度增强

Abstract:

Keywords:

基金项目(Foundation): 陕西省自然科学基础研究计划项目(2019JM-492)

作者(Authors): 卢才武;马玲;阮顺领;

DOI: 10.16251/j.cnki.1009-2307.2020.09.019

参考文献(References)：

• [1] SHANG E,AN X,YE L,et al.Unstructured road detection based on hybrid features[Z].[S.l.:s.n.],2014.
• [2] HUANG KONG,LI B,et al.A new method of unstructured road detection based on HSV color space and road features[C]//International Conference on Information Acquisition.[S.l.]:IEEE,2017.
• [3] 刘富,袁雨桐,李洋.基于纹理特征的非结构化道路分割算法[J].计算机应用,2015,35(S2):271-273.(LIU Fu,YUAN Yutong,LI Yang.Texture-based unstructured road segmentation algorithm[J].Computer Applications,2015,35(S2):271-273.)
• [4] 李骏扬,金立左,费树岷.基于多尺度特征表示的城市道路检测[J].电子与信息学报,2014(11):2578-2585.(LI Junyang,JIN Lizuo,FEI Shumin.Urban road detection based on multi-scale feature representation[J].Journal of Electronics and Information,2014(11):2578-2585.)
• [5] 柏猛,李敏花.基于图模型的道路检测方法[J].模式识别与人工智能,2014,27(7):655-662.(BAI Meng,LI Minhua.Road detection method based on graph model[J].Pattern Recognition and Artificial Intelligence,2014,27(7):655-662.)
• [6] XING Y,LYU C,CHEN L,et al.Advances in vision-based lane detection:algorithms,integration,assessment,and perspectives on ACP-Based parallel vision[J].IEEE/CAA Journal of Automatica Sinica,2018,5(3):645-661.
• [7] 龚建伟,叶春兰,姜岩,等.多层感知器自监督在线学习非结构化道路识别[J].北京理工大学学报,2014,34(3):261-266.(GONG Jianwei,YE Chunlan,JIANG Yan,et al.Multi-layer perceptron self-supervised online learning for unstructured road recognition[J].Journal of Beijing University of Technology,2014,34(3):261-266.)
• [8] ZHOU S Y,GONG J W,XIONG G M,et al.Road detection using support vector machine based on online learning and evaluation[C]//IEEE Intelligent Vehicles Symposium.San Diego,CA,USA:IEEE,2010:256-261.
• [9] 周植宇,杨明,薛林继,等.一种基于高斯核支持向量机的非结构化道路环境植被检测方法[J].机器人,2015,37(6):702-707.(ZHOU Zhiyu,YANG Ming,XUE Linji,et al.An unstructured road environment vegetation detection method based on Gauss kernel support vector machine[J].Robot,2015,37(6):702-707.)
• [10] 罗文婷,李中轶,李林,等.基于改进Canny边缘检测算法的道路标线自动识别及定位[J].西南交通大学学报,2018,53(6):1253-1260.(LUO Wenting,LI Zhongyi,LI Lin,et al.Road marking automatic recognition and location based on improved Canny edge detection algorithm[J].Journal of Southwest Jiaotong University,2018,53(6):1253-1260.)
• [11] 熊思,李磊民,黄玉清.基于小波变换和K-means的非结构化道路检测[J].计算机工程,2014,40(2):158-161.(XIONG Si,LI Leimin,HUANG Yuqing.Unstructured road detection based on wavelet transform and K-means[J].Computer Engineering,2014,40(2):158-161.)
• [12] 吴骅跃,段里仁.RGB熵和改进区域生长的非结构化道路识别方法[J].吉林大学学报(工学版):2019,49(3):727-735.(WU Huayue,DUAN Liren.RGB entropy and unstructured road recognition method for improving regional growth[J].Journal of Jilin University (Engineering Edition):2019,49(3):727-735.)
• [13] 杨春德,郭帅.改进基于HSV空间的阴影检测算法[J].计算机工程与设计,2018,39(1):255-259.(YANG Chunde,GUO Shuai.Improved shadow detection algorithm based on HSV space[J].Computer Engineering and Design,2018,39(1):255-259.)
• [14] 彭明阳,王建华,闻祥鑫,等.结合HSV空间的水面图像特征水岸线检测[J].中国图象图形学报,2018,23(4):526-533.(PENG Mingyang,WANG Jianhua,WEN Xiangxin,et al.Waterfront detection based on water surface image features in HSV space[J].Chinese Journal of Image Graphics,2018,23(4):526-533.)
• [15] 刘桂红,赵亮,孙劲光.一种改进粒子群优化算法的Otsu 图像阈值分割方法[J].计算机科学,2016,43(3):309-312.(LIU Guihong,ZHAO Liang,SUN Jinguang.An improved particle swarm optimization method for Otsu image threshold segmentation[J].Computer Science,2016,43(3):309-312.)
• [16] CANNY J.A computational approach to edge detecti[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1986,8(6):679-69.