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Ship infrared image edge detection based on an improved adaptive Canny algorithm

Author

Listed:
  • Lisang Liu
  • Fenqiang Liang
  • Jishi Zheng
  • Dongwei He
  • Jing Huang

Abstract

Influenced by light reflection and water fog interference, ship infrared images are mostly blurred and have low signal-to-noise ratio. In this paper, an improved adaptive Canny edge detection algorithm for infrared image of ship is proposed, which aims to solve the threshold of the traditional Canny cannot be adjusted automatically and the shortcomings of sensitivity to noise. The contrast limited adaptive histogram equalization algorithm is adopted to enhance the infrared image, the morphological filter replaces the Gauss filter to smooth the image, and the OTSU algorithm is utilized to adjust the high and low thresholds dynamically. The experimental results show that the improved Canny algorithm, which can not only improve the contrast of the image and automatically adjust the threshold but also reduce the background sea clutter and false edges, is an effective edge detection method.

Suggested Citation

  • Lisang Liu & Fenqiang Liang & Jishi Zheng & Dongwei He & Jing Huang, 2018. "Ship infrared image edge detection based on an improved adaptive Canny algorithm," International Journal of Distributed Sensor Networks, , vol. 14(3), pages 15501477187, March.
    • Handle: RePEc:sae:intdis:v:14:y:2018:i:3:p:1550147718764639
    DOI: 10.1177/1550147718764639
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    Cited by:

    1. Chi Yoon Jeong & Hyun S Yang & KyeongDeok Moon, 2018. "Fast horizon detection in maritime images using region-of-interest," International Journal of Distributed Sensor Networks, , vol. 14(7), pages 15501477187, July.

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