Unstructured road segmentation based on Otsu-entropy method

Chaoxia Shi; Yanqing Wang; Hanxiang Liu; Jingyu Yang

doi:10.1117/12.910650

28 October 2011 Unstructured road segmentation based on Otsu-entropy method

Chaoxia Shi, Yanqing Wang, Hanxiang Liu, Jingyu Yang

Proceedings Volume 8205, 2011 International Conference on Photonics, 3D-Imaging, and Visualization; 820509 (2011) https://doi.org/10.1117/12.910650
Event: 2011 International Conference on Photonics, 3D-imaging, and Visualization, 2011, Guangzhou, China

Abstract

Unstructured road segmentation plays an important role in visual guiding navigation for intelligent vehicle. A novel vision-based road segmentation method that combined the Otsu double-threshold method with the maximum entropy double-threshold method was proposed to handle those problems caused by illumination variations and road surface dilapidation. Spatial correlation by analyzing the grey-level histogram of the original image and temporal correlation by matching of the selected referenced region was used to estimate the coarse range of the road region. Road segmentation experiments executed in different road scenes have demonstrate that the method proposed in this paper is robust against illumination variations and surface dilapidation.

Citation Download Citation

Chaoxia Shi, Yanqing Wang, Hanxiang Liu, and Jingyu Yang "Unstructured road segmentation based on Otsu-entropy method", Proc. SPIE 8205, 2011 International Conference on Photonics, 3D-Imaging, and Visualization, 820509 (28 October 2011); https://doi.org/10.1117/12.910650

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KEYWORDS

Roads

Image segmentation

Image information entropy

Lithium

Probability theory

Visualization

3D modeling

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