Volume 42 Issue 1
Feb.  2014
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Wan Lei, Zeng Wenjing, Zhang Tiedong, Qin Zaibai. Real-time detection of marine infrared objects based on the fusion of gradient information[J]. Infrared and Laser Engineering, 2013, 42(1): 41-45.
Citation: Wan Lei, Zeng Wenjing, Zhang Tiedong, Qin Zaibai. Real-time detection of marine infrared objects based on the fusion of gradient information[J]. Infrared and Laser Engineering, 2013, 42(1): 41-45.

Real-time detection of marine infrared objects based on the fusion of gradient information

  • Received Date: 2012-05-07
  • Rev Recd Date: 2012-06-11
  • Publish Date: 2013-01-25
  • A feasible method considering the character of marine infrared image was proposed to detect objects in the sequential images from surface vehicle, which was not only appropriate for sea-sky background but also for offshore background. There was no need to filter the noise. Firstly, the complexity of sub-images and the average gray difference of their up and down neighborhood were measured to predict the sea line region. Secondly, improved Canny edge detection was applied to extract the contour of the sea line region. It made the sea line obvious and meaningless edges disappear greatly. Thirdly, Hough transformation was used to pick the longest line as the sea line. Finally, a kind of general concept of gradient was put forward. The targets could be marked excellently under the fusion of gradient. The experiment results show that this method can locate the sea-line region and the sea line with any tilt reliably and obtain the information of objects effectively. The whole procedure costs about 60 ms and it is real-time and robust.
  • [1] Wang Lidi,Huang Shabai,Shi Zelin. Automatic detection of the infrared small sea target based on wavelet and fractal[J]. Laser Infrared, 2004, 34(6): 481-484. (in Chinese)
    [2]
    [3] Wei Ying, Shi Zelin, Li Chengjun, et al. Detection algorithm for infrared small target in background of sea and sky[J]. Infrared and Laser Engineering, 2003, 32(2): 153-156. (in Chinese)
    [4] 王立地, 黄莎白, 史泽林. 基于小波和分形的海面红外小目标自动检测方法[J]. 激光与红外, 2004, 34(6): 481-484.
    [5] Yang Lei, Yang Jie, Zheng Zhonglong. Detecting infrared small targets based on adaptive local energy threshold under sea-sky complex background[J]. J Infrared Millim Waves,2006, 25(1): 42-46. (in Chinese)
    [6]
    [7] Pan Yuzhu, Huang Shunhuan, Li Chisheng. Detection of infrared small target based on UDWT[J]. Laser Infrared, 2009, 39(11): 1237-1240. (in Chinese)
    [8]
    [9] Yang L, Zhou Y, Yang J, et al. Variance WIE based infrared images processing[J]. Electronics Letters, 2006, 42(15): 857-859.
    [10] 魏颖, 史泽林, 李成军, 等. 海空背景下红外小目标检测算法[J]. 红外与激光工程, 2003, 32(2): 153-156.
    [11] Liu Yuanyuan, Liu Wenbo, Zhen Ziyang. Image segmentation method based on fuzzy entropy and grey relational analysis[J]. Journal of OptoelectronicsLaser, 2008, 19(9): 1250-1253. (in Chinese)
    [12]
    [13] Zhu Shiping, Xia Xi, Zhang Qingrong. An edge detection algorithm in image processing based oil point-by-point threshold segmentation[J]. Journal of OptoelectronicsLaser,2008, 19(10): 1383-1387. (in Chinese)
    [14]
    [15] 杨磊, 杨杰, 郑忠龙. 海空复杂背景中基于自适应局部能量阈值的红外小目标检测[J]. 红外与毫米波学报, 2006, 25(1): 42-46.
    [16] Cosmin Grigorescu, Nicolai Petkov, Michel A Westenberg. Contour and boundary detection improved by surround suppression of texture edges[J]. Image and Vision Computing, 2004, 22(8): 609-622.
    [17] Guo Siyu, Pridmore Tony, Kong Yaguang, et al. An improved Hough transform voting scheme utilizing surround suppression[J]. Pattern Recognition Letters, 2009, 30(13): 1241-1252.
    [18]
    [19]
    [20] Ray Hidayat. Texture-boundary detection in real-time[D]. Christchurch: University of Canterbury, 2010: 75-76.
    [21] 潘玉竹, 黄顺欢, 李迟生. 基于非抽样小波的红外小目标检测[J]. 激光与红外, 2009, 39 (11): 1237-1240.
    [22]
    [23]
    [24]
    [25] 刘媛媛, 刘文波, 甄子洋. 灰色关联度和模糊熵相结合的图像分割算法[J]. 光电子激光, 2008, 19(9): 1250-1253.
    [26]
    [27]
    [28] 祝世平, 夏曦, 张庆荣. 一种基于逐点闽值分割的图像边缘检测方法[J]. 光电子激光, 2008, 19(10): 1383-1387.
    [29]
    [30]
    [31]
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Real-time detection of marine infrared objects based on the fusion of gradient information

  • 1. State Key Laboratory of Autonomous Underwater Vehicle,Harbin Engineering University,Harbin 150001,China

Abstract: A feasible method considering the character of marine infrared image was proposed to detect objects in the sequential images from surface vehicle, which was not only appropriate for sea-sky background but also for offshore background. There was no need to filter the noise. Firstly, the complexity of sub-images and the average gray difference of their up and down neighborhood were measured to predict the sea line region. Secondly, improved Canny edge detection was applied to extract the contour of the sea line region. It made the sea line obvious and meaningless edges disappear greatly. Thirdly, Hough transformation was used to pick the longest line as the sea line. Finally, a kind of general concept of gradient was put forward. The targets could be marked excellently under the fusion of gradient. The experiment results show that this method can locate the sea-line region and the sea line with any tilt reliably and obtain the information of objects effectively. The whole procedure costs about 60 ms and it is real-time and robust.

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