• Electronics Optics & Control
  • Vol. 24, Issue 2, 43 (2017)
AI Shu-fang1, YAN Jun-hua1、2, LI Da-lei1, XU Jun-feng2, and SHEN Jing2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2017.02.009 Cite this Article
    AI Shu-fang, YAN Jun-hua, LI Da-lei, XU Jun-feng, SHEN Jing. An Algorithm for Detecting the Airport Runway in Remote Sensing Image[J]. Electronics Optics & Control, 2017, 24(2): 43 Copy Citation Text show less

    Abstract

    The characteristics of high grey-scale and integrality of the airport runways are used for detecting them in remote sensing image.Firstly, the image was pre-processed by using fuzzy enhancement.Secondly, binary image was obtained though threshold segmentation, and pixel labeling method was used for connected area extraction, thus the largest four areas were chosen as suspected airport areas, which were then located.Then, within these four suspected airport areas, edges were detected on the image by using Canny edge detection operator, and straight line segments were extracted by using Hough transform.Finally, the area with the longest parallel lines was recognized as the airport area.Experimental results show that by using the airport runway detection algorithm, the airport runways in remote sensing image can be detected efficiently and accurately.
    AI Shu-fang, YAN Jun-hua, LI Da-lei, XU Jun-feng, SHEN Jing. An Algorithm for Detecting the Airport Runway in Remote Sensing Image[J]. Electronics Optics & Control, 2017, 24(2): 43
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