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Vehicle Detection Based on Binocular Stereovision and Edge Extraction

机译:基于双目立体宽度和边缘提取的车辆检测

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Traffic accident has already become a significant social problem. Intelligent Transportation Systems (ITS) is vital to improve the vehicle safety. As an important part of ITS, vehicle detection has been widespread concern. This paper presents a vehicle detection algorithm based on binocular stereovision and edge extraction: analyze spatial coordinate feature belong to object point and detect obstacle points; segment Region of Interest; apply symmetry to detect vehicle. The experimental results indicate that the algorithm possess high efficiency and accuracy.
机译:交通事故已经成为一个重要的社会问题。 智能交通系统(其)对于提高车辆安全至关重要。 作为其重要部分,车辆检测令人普遍的担忧。 本文介绍了一种基于双目立体宽度和边缘提取的车辆检测算法:分析空间坐标特征属于对象点并检测障碍点; 群体地区; 应用对称以检测车辆。 实验结果表明该算法具有高效率和准确性。

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