基于轮廓分割的阴影道路检测

2020 22th International Conference on Digital Signal Processing and its Applications (DSPA) Pub Date : 2020-03-01 DOI:10.1109/DSPA48919.2020.9213290

E. Kurbatova, Y. Pavlovskaya

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引用次数: 1

摘要

本文研究了被周围物体投射的阴影遮挡部分道路的检测问题。该方法包括三个主要步骤:预处理、阴影检测和去除、道路检测。阴影和道路的检测是基于HSV色彩空间的轮廓分割。轮廓分割后，H分量被分割成段。计算每个片段的特征值，并与阈值进行比较。亮度被用作阴影检测的特征。道路检测基于颜色特征。用伽马校正法去除阴影。实验结果证明了该方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Shaded Roads Detection Based on Contour Segmentation

This paper deals with the detection of roads partially obscured by shadows that are cast by neighboring objects. The approach consists of three main steps: preprocessing, shadow detection and removal, and road detection. Detection of shadows and roads is based on contour segmentation in HSV color space. After contour segmentation, the H component is divided into segments. The value of a feature is calculated for each segment and is compared with the threshold. Brightness is used as a feature for shadow detection. Road detection is based on the color feature. The gamma correction method is used for shadow removal. Experimental results demonstrate the effectiveness of the proposed approach.

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来源期刊

2020 22th International Conference on Digital Signal Processing and its Applications (DSPA)

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