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Detection of Road Image Borders Based on Texture Classification

机译:基于纹理分类的道路图像边界检测

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The concept of an algorithm developed for the segmentation of a road border from the content of an image produced by a forward looking TV camera mounted on a moving vehicle is presented in this paper. The extraction of a road boundary is an important step in the context of autonomous vehicle guidance, enabling further calculations of distance from the border, direction of a road, etc. The main idea behind this approach is that the texture of a road is different enough in comparison to the textures characterizing the surrounding environment, allowing the separation of the overall image into a few distinguishable regions. The segmentation algorithm combines the texture descriptors of a statistical nature and the ones based on a grey level co-occurrence matrix. The significance of this work is mainly in the practical verification of the proposed algorithm and in the testing of the real limits of its application.
机译:本文提出了一种算法的概念,该算法可从安装在行驶中的车辆上的前视电视摄像机产生的图像内容中分割出道路边界。道路边界的提取是自动驾驶车辆引导中的重要步骤,可以进一步计算与边界的距离,道路方向等。此方法的主要思想是,道路的纹理足够不同与表征周围环境的纹理相比,可以将整个图像分为几个可区分的区域。分割算法结合了统计性质的纹理描述符和基于灰度共生矩阵的纹理描述符。这项工作的意义主要在于对所提出算法的实际验证以及对其应用的实际限制的测试。

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