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首页> 外文会议>International Conference on Machine Vision >A Study on Low-Cost, High-Accuracy and Real-Time Stereo Vision Algorithms for UAV Power Line Inspection
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A Study on Low-Cost, High-Accuracy and Real-Time Stereo Vision Algorithms for UAV Power Line Inspection

机译：低成本，高精度和实时立体声视觉视觉算法的研究

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Conventional stereo vision algorithms suffer from high levels of hardware resource utilization due to algorithm complexity, or poor levels of accuracy caused by inadequacies in the matching algorithm. To address these issues, we have proposed a stereo range-finding technique that produces an excellent balance between cost, matching accuracy and real-time performance, for power line inspection using UAV. This was achieved through the introduction of a special image preprocessing algorithm and a weighted local stereo matching algorithm, as well as the design of a corresponding hardware architecture. Stereo vision systems based on this technique have a lower level of resource usage and also a higher level of matching accuracy following hardware acceleration. To validate the effectiveness of our technique, a stereo vision system based on our improved algorithms were implemented using the Spartan 6 FPGA. In comparative experiments, it was shown that the system using the improved algorithms outperformed the system based on the unimproved algorithms, in terms of resource utilization and matching accuracy. In particular, Block RAM usage was reduced by 19%, and the improved system was also able to output range-finding data in real time.
机译：传统的立体视觉算法由于算法复杂性而受到高水平的硬件资源利用率，或者在匹配算法中不足引起的准确度差。为解决这些问题，我们提出了一种立体声测距技术，可以使用无人机的电力线检查在成本，匹配精度和实时性能之间产生优异的平衡。这是通过引入特殊的图像预处理算法和加权本地立体声匹配算法来实现的，以及相应的硬件架构的设计。基于该技术的立体视觉系统具有较低水平的资源使用量，并且在硬件加速度之后的匹配精度也更高。为了验证我们技术的有效性，使用Spartan 6 FPGA来实现基于我们改进算法的立体视觉系统。在比较实验中，示出了使用改进算法的系统基于资源利用率和匹配精度来基于未改良的算法来表现出基于未改良的算法的系统。特别地，块RAM使用率降低了19％，并且改进的系统也能够实时输出范围查找数据。

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