摘要
In the research of automated driving technology, a vision-based road width measurement method is proposed to quickly detect the road and measure the width of the road. Firstly, an improved Deeplabv3+ semantic segmentation algorithm is proposed to improve the accuracy of road edge segmentation by introducing the attention mechanism based on spatial domain into the original algorithm flow. Secondly, a semi-global stereo matching algorithm combining histogram equalization and weighted most minor square filtering is proposed, which can significantly improve the matching accuracy of object edge details in images. Then, a road width measurement system based on the proposed method is proposed. The system is mounted on an autonomous vehicle to complete the segmentation and width measurement of the road in the global image. The experimental results show that the measurement error of the proposed algorithm is less than 5.0% of the real value.
投稿的翻译标题 | A vision based road width measurement method |
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源语言 | 繁体中文 |
页(从-至) | 218-223 |
页数 | 6 |
期刊 | Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology |
卷 | 30 |
期 | 2 |
DOI | |
出版状态 | 已出版 - 4月 2022 |
关键词
- Deeplabv3+
- Semantic segmentation
- Stereo matching
- Visual measurement