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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2015  >  15(4): 110-117
LIU Sheng, WANG Wei-xing, WANG Shan-shan, HAN Ya, HUANG Ling-xiao, ZHANG Xin. Automatic detection method of roads from fuzzy aerial images[J]. Journal of Traffic and Transportation Engineering, 2015, 15(4): 110-117. doi: 10.19818/j.cnki.1671-1637.2015.04.014
Citation: LIU Sheng, WANG Wei-xing, WANG Shan-shan, HAN Ya, HUANG Ling-xiao, ZHANG Xin. Automatic detection method of roads from fuzzy aerial images[J]. Journal of Traffic and Transportation Engineering, 2015, 15(4): 110-117. doi: 10.19818/j.cnki.1671-1637.2015.04.014
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Automatic detection method of roads from fuzzy aerial images

doi: 10.19818/j.cnki.1671-1637.2015.04.014

  • School of Information Engineering, Chang'an University Xi'an 710064, Shaanxi, China

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  • Author Bio:

    LIU Sheng(1980-), female, doctoral student, +86-29-82520922, ls7691010@126.com

    WANG Wei-xing(1959-), male, professor, PhD, +86-29-82334562, wxwang@chd.edu.cn

  • Received Date: 2015-02-25
  • Publish Date: 2015-04-25
    Abstract
  • In order to accurately detect the road from fuzzy aerial images, an automatic road detection method was proposed based on the characteristics of roads in images.The fuzzy images were enhanced by using multiple scale Retinex algorithm.The main road segments in images were detected by using improved Canny edge detection algorithm, and the high and low thresholds in gradient images were automatically obtained by using cross-entropy theory and Bayesian judgment theory, the gray image was transformed into the binary images, and the skeletons of linear target in the image were extracted.The noise was filtered based on the shape and size characteristics in the linear target, the gaps between segments were linked based on the curvature and the distances between segments, and the detected road was adjusted and modified by combing the edge and the original image information.The proposed automatic road detection method was compared with several widely used traditional algorithms, such as Otsu threshold segmentation algorithm, Canny edge detection algorithm, and graph theory based on the minimum segmentation algorithm.a single road, cross roads and several roads in fuzzy images were detected by using the proposed road detection method.Detection result indicates that as forfuzzy or uneven-illumination aerial road images, the trunk roads can be clearly displayed after enhancing images by Retinex algorithm, while the conventional image segmentation algorithm can not do.The trunk road can be well extracted by using the improved Canny edge detection algorithm with image post-processing function.In the detection of single road, cross roads and several roads in the fuzzy aerial images, the target roads can be clearly detected by using the proposed method.The effect of detection method is close to the result of artificial recognition.

     

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