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Volume 43 Issue 9
Sep.  2021
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HE Qian, LIU Boyun. Improved Infrared Image Edge Detection Algorithm Based on DexiNed[J]. Infrared Technology , 2021, 43(9): 876-884.
Citation: HE Qian, LIU Boyun. Improved Infrared Image Edge Detection Algorithm Based on DexiNed[J]. Infrared Technology , 2021, 43(9): 876-884.
shu

Improved Infrared Image Edge Detection Algorithm Based on DexiNed

  • College of Power Engineering, Naval University of Engineering, Wuhan 430033, China

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  • Received Date: March 22, 2021
  • Revised Date: April 15, 2021
    Graphical Abstract
    • Abstract
  • Compared with optical image edge detection, there are fewer studies on infrared image edge detection, and most of them are based on traditional methods, such as edge detection operators and mathematical morphology. In essence, they only consider the sharp local changes of infrared images to detect edges, so they are always limited by low-level features. In this paper, an infrared image edge detection algorithm based on deep learning is proposed. Based on the dense extreme inception network for edge detection (DexiNed), the network capacity is reduced by removing the last main block, the image level difference is introduced into the loss function, and the parameters of the loss function are carefully set to optimize the network performance. In addition, by adjusting the natural image edge detection dataset to approximate the infrared image edge detection dataset, the improved model was trained to enhance the edge detection ability. The qualitative evaluation results show that the edge of the infrared image extracted by our method is accurate, precise, rich in detail, and fits human vision. A quantitative evaluation using the structural similarity indexmatrix (SSIM) and feature similarity indexmatrix (FSIM) indexes further shows the advantages of our method compared with other existing methods.
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    • References (26)
  • [1]
    夏清, 胡振琪, 位蓓蕾, 等. 一种新的红外热像仪图像边缘检测方法[J]. 红外与激光工程, 2014, 43(1): 318-322. DOI: 10.3969/j.issn.1007-2276.2014.01.056

    XIA Qing, HU Zhenqi, WEI Beilei, et al. New edge detection method for images of infrared thermal imager[J]. Infrared and Laser Engineering, 2014, 43(1): 318-322. DOI: 10.3969/j.issn.1007-2276.2014.01.056
    [2]
    唐庆菊, 刘俊岩, 王扬, 等. 基于模糊C均值聚类和Canny算子的红外图像边缘识别与缺陷定量检测[J]. 红外与激光工程, 2016, 45(9): 281-285. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ201609042.htm

    TANG Qingju, LIU Junyan, WANG Yang, et al. Infrared image edge recognition and defect quantitative determination based on the algorithm of fuzzy C-means clustering and Canny operator[J]. Infrared and Laser Engineering, 2016, 45(9): 281-285. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ201609042.htm
    [3]
    Minh V H, Aleef T A, Pervaiz U, et al. Smoothness-based Edge Detection using Low-SNR Camera for Robot Naviga-tion[J/OL]. arXiv preprint arXiv: 1710.01416, 2017.
    [4]
    LIU Lisang, LIANG Fenqiang, ZHENG Jishi, et al. Ship infrared image edge detection based on an improved adaptive Canny algorithm[J]. International Journal of Distributed Sensor Networks, 2018, 14(3): 51-57. http://www.onacademic.com/detail/journal_1000040876503810_4fec.html
    [5]
    QIAO B M, LI S, XIAO Y. Infrared image edge detection applied research based on improved ant colony algorithm[C]//Proceedings of the 2015 International conference on Applied Science and Engineering Innovation, 2015: 31.
    [6]
    王凤. 结合蚁群搜索与边缘检测的红外轮廓提取算法[J]. 激光与红外, 2015, 45(6): 722-727. DOI: 10.3969/j.issn.1001-5078.2015.06.025

    WANG Feng. Infrared contour extraction algorithm based on ants search and edge detection[J]. Laser & Infrared, 2015, 45(6): 722-727. DOI: 10.3969/j.issn.1001-5078.2015.06.025
    [7]
    ZHANG X, HAN R. The Application of Mathematical Morphology and Sobel Operator in Infrared Image Edge Detection[C]//International Industrial Informatics & Computer Engineering Conference, 2015: 949-954.
    [8]
    YIN J, LU Y, GONG Z, et al. Edge Detection of High-Voltage Porcelain Insulators in Infrared Image Using Dual Parity Morphological Gradients[J]. IEEE Access, 2019, 26(7): 32728-32734. http://www.onacademic.com/detail/journal_1000042299647699_6769.html
    [9]
    Bertasius G, SHI J, Torresani. Deep Edge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour Detection[C]//Computer Vision & Pattern Recognition. IEEE, 2015: 4380-4389.
    [10]
    XIE S, TU Z. Holistically-nested edge detection[C]//Proceedings of the IEEE international conference on computer vision, 2015: 1395-1403.
    [11]
    LIU Y, CHENG M M, HU X, et al. Richer convolutional features for edge detection[C]//Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference, 2017: 5872-5881.
    [12]
    HE J, ZHANG S, YANG M, et al. Bidirectional cascade network for perceptual edge detection[J/OL]. arXiv preprint arXiv: 1902.10903, 2019.
    [13]
    DENG R, SHEN C, LIU S, et al. Learning to predictcrisp boundaries [C]//European Conference on Computer Vision, 2018: 1-17.
    [14]
    Xavier Soria, Edgar Riba, Angel D. Sappa. Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection[J/OL]. arXiv preprint arXiv: 1909.01955v2, 2020.
    [15]
    焦安波, 何淼, 罗海波. 一种改进的HED网络及其在边缘检测中的应用[J]. 红外技术, 2019, 41(1): 72-77. http://hwjs.nvir.cn/article/id/hwjs201901011

    JIAO Anbo, HE Miao, LUO Haibo. Research on Significant Edge Detection of Infrared Image Based on Deep Learning[J]. Infrared Technology, 2019, 41(1): 72-77. http://hwjs.nvir.cn/article/id/hwjs201901011
    [16]
    Mely D A, Kim J, McGill M, et al. A systematic comparison between visual cues for boundary detection[J]. Vision Research, 2016, 120: 93-107. DOI: 10.1016/j.visres.2015.11.007
    [17]
    Grigorescu C, Petkov N, Westenberg M A. Contour detection based on nonclassical receptive field inhibition[J]. IEEE Transactions on image processing, 2003, 12(7): 729-739. DOI: 10.1109/TIP.2003.814250
    [18]
    Martin D, Fowlkes C, Tal D, et al. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics[C]//Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, 2: 416-423.
    [19]
    Arbelaez P, Maire M, Fowlkes C, et al. Contour detection and hierarchical image segmentation[J]. IEEE Trans. Pattern Anal. Mach. Intell., 2011, 33(5): 898-916. DOI: 10.1109/TPAMI.2010.161
    [20]
    Silberman N, HoiemD, Kohli P, et al. Indoor segmentation and support inference from RGBD images[C]//European Conference on Computer Vision, 2012: 746-760.
    [21]
    Mottaghi R, CHEN X, LIU X, et al. The role of context for object detection and semantic segmentation in the wild[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014: 891-898.
    [22]
    Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[J/OL]. arXiv preprint arXiv: 1409.1556, 2014.
    [23]
    LI N, SU Z, CHEN Z, et al. A real-time aircraft infrared imaging simulation platform[J]. Optik International Journal for Light & Electron Optics, 2013, 124(17): 2885-2893. http://or.nsfc.gov.cn/bitstream/00001903-5/94940/1/1000006643792.pdf
    [24]
    Davis J, Keck M. A Two-Stage Template Approach to Person Detection in Thermal Imagery[C]// 2005 Seventh IEEE Workshops on Applications of Computer Vision, 2005, 1: 364-369.
    [25]
    WANG Z, Bovik A C, Sheikh H R, et al. Image quality assessment: from error visibility to structural similarity[J]. IEEE Trans Image Process, 2004, 13(4): 967-981. http://citeseer.ist.psu.edu/viewdoc/download;jsessionid=1CEF39B23BCE926AD6D155479B134452?doi=10.1.1.11.2477&rep=rep1&type=pdf
    [26]
    ZHANG L, ZHANG L, MOU X, et al. FSIM: A Feature Similarity Index for Image Quality Assessment[J]. IEEE Transactions on Image Processing, 2011, 20(8): 2378-2386. DOI: 10.1109/TIP.2011.2109730
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