基于融合动态模板匹配的双目测距算法
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陕西省科技统筹创新工程计划(2015KTZDGY-02-01);陕西省科技厅重点项目(2017JY-045);陕西省教育厅科研计划项目(17JK0386)


Binocular Ranging Algorithm Based on Fusion Dynamic Template Matching
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    摘要:

    高空无人机灭火时,要对火灾点进行探测.传统的探测方法易受环境的干扰,并且它的反应不灵敏,实时性较差.基于此本文提出了一种基于双目立体视觉的探测方法:首先搭建实验平台并设计其硬件电路,然后深入研究了经典的双目立体视觉测距算法,提出了一种新的测距方法.该方法主要内容包括:图像获取、感兴趣区域提取、图像预处理和基于权重融合的动态模板匹配算法.最后,采用多段非线性补偿的方法构建了测距模型,并在实验平台上对所构建的测距模型进行了大量的实验,实验结果表明:在50 m以内,该测距模型的误差在1 m以内,100 m以内,测距误差在2 m,匹配精度为6.947像素/m,基本符合高空无人机灭火的精确测距要求,故该测距模型测量的距离精度较好,工程应用性强.

    Abstract:

    When the high altitude unmanned aerial vehicle is extinguishing, it is necessary to detect the fire point. The traditional detection method is easily disturbed by the environment, its reaction is insensitive and its real-time feature is poor. Therefore, a new method based on binocular stereo vision is proposed in this study. First, we set up the experiment platform and design the hardware circuit. Then the classical binocular stereo vision ranging algorithm is studied deeply, and a new method of distance measurement is proposed. The method mainly includes:image acquisition, region of interest extraction, image preprocessing, and dynamic template matching based on the weight fusion. Finally, the multi segment nonlinear compensation method is used to construct the distance measurement model, and a large number of experiments are carried out on the experimental platform. The experimental result show that within 50 meters, the error of the ranging model is better than 1 meter, and within 100 meters, the ranging error is better than 2 meters, the matching precision is 6.947 pixels/m. The result basically meets the requirement of precise ranging for high altitude UAV fire extinguishing, so the distance measurement accuracy of the ranging model and the engineering application are both good.

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史珂路,田军委,雷志强,张欢欢,孙雷.基于融合动态模板匹配的双目测距算法.计算机系统应用,2018,27(11):218-223

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  • 收稿日期:2018-04-16
  • 最后修改日期:2018-05-08
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  • 在线发布日期: 2018-10-24
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