基于最大熵和边缘信息的非结构化道路检测

doi:10.16180/j.cnki.issn1007-7820.2020.01.005

Abstract

Abstract:

Aiming at the problem that the unstructured roads are difficult to accurately detect due to the various scene interference factors, an unstructured road detection algorithm based on the combination of maximum entropy and edge information was proposed. In this paper, the two-dimensional maximum entropy was used for the initial segmentation of the road because of the fact that the gray level of the high entropy fields of image was relatively uniform and vice versa. Furthermore, the road edge information was applied to further improve the inaccurate problem of road detection caused by uneven illumination, shadow and water stain. The experimental results indicated that the algorithm could accurately detect the road surface with light, shadow and water without the effect of the road environment and meet requirements of real-time.

Key words: unstructured road, two-dimensional maximum entropy, edge detection, morphological filtering, road segmentation, random consistency algorithm

CLC Number:

TP751

WANG Xiang,ZHANG Juan,FANG Zhijun. Unstructured Road Detection Based on Edge Information and Maximum Entropy Segmentation[J].Electronic Science and Technology, 2020, 33(1): 23-28.

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Unstructured Road Detection Based on Edge Information and Maximum Entropy Segmentation

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