郑晓亮,周晓,欧科君,牟新刚.基于TCensus的立体匹配算法及FPGA设计[J].国外电子测量技术,2017,36(7):71-76
基于TCensus的立体匹配算法及FPGA设计
Stereo matching algorithm and FPGA design based on TCensus
  
DOI:
中文关键词:  立体匹配  无人机电力巡线  图像增强  Tophat变换
英文关键词:stereo matching  UAV power line inspection  image enhancement  Tophat transformation
基金项目:
作者单位
郑晓亮 武汉理工大学机电工程学院 武汉 430070 
周晓 武汉理工大学机电工程学院 武汉 430070 
欧科君 武汉理工大学机电工程学院 武汉 430070 
牟新刚 武汉理工大学机电工程学院 武汉 430070 
AuthorInstitution
Zheng Xiaoliang Institute of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China 
Zhou Xiao Institute of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China 
Ou Kejun Institute of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China 
Mu Xingang Institute of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China 
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中文摘要:
      随着无人机技术的迅速发展,利用无人机代替人工进行电力线巡线是行业内发展的新趋势。尽管无人机电力巡线相对于人工巡检效率更高,更加安全,但无人机巡检仍然面临一些问题,无人机的避障技术亟待完善,在巡检过程中无人机会出现与周边障碍物相撞的情况,尤其是细小的电线对无人机安全造成巨大的威胁。这些线状物往往目标不明显,雷达,超声波等技术得到的回波较少,造成避障困难。基于双目视觉系统的无人机避障技术在无人机避障领域得到了广泛的研究和关注。针对双目视觉实时无人机电力巡检避障应用,提出了基于TCensus(形态学Tophat变换和MiniCensus)变换的匹配代价测量方法来对原始图像中的弱目标进行增强,同时采用基于十字结构的支持区域来提高匹配的准确度。实验证明,本文设计的双目视觉系统可以有效检测无人机到电力线之间的距离,检测误差达到5%,提出的TCensus立体匹配算法与其它方法相比除了能够获得同样准确的背景深度图之外,还能对电线区域具有更精细的成像效果。
英文摘要:
      With the rapid development of UAV technology, the use of unmanned aerial vehicles instead of artificial power line inspection line is the industry development trend. Although UAV power patrols are more efficient and safer than manual inspection, UAV inspection continues to face problems such as aviation restrictions, airborne weight, flight life, obstacle avoidance technology and other factors. Unmanned aerial vehicle obstacle avoidance technology needs to be improved, in the inspection process, no chance will appear with the surrounding obstacles collision situation, and especially the small wires on the UAV caused a huge threat. These lines are often not obvious targets, radar, ultrasound and other technologies to get less echo, resulting in obstacle avoidance difficulties. The UAV obstacle avoidance technology based on binocular vision system has been widely studied and paid attention to in the field of unmanned aerial vehicles. This paper designs a real time UAV power line detection system based on binocular vision system. In this paper, a matching cost measurement method based on TCensus (morphological Tophat transform and MiniCensus) is proposed to enhance the weak target in the original image, and the support region based on the cross structure is used to improve the matching accuracy. The experimental results show that the binocular vision system can effectively detect the distance between the UAV and the power line, and the detection error is 5%. The stereo matching algorithm proposed in this paper can obtain a better depth map, and the TCensus algorithm can effectively preserve the original image in the weak target line information.
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