WANG Xingbin, ZHANG Jun, WANG Shuaihui, “The Cat's Eye Effect Target Recognition Method Based on Visual Attention,” Chinese Journal of Electronics, vol. 28, no. 5, pp. 1080-1086, 2019, doi: 10.1049/cje.2019.06.027
Citation: WANG Xingbin, ZHANG Jun, WANG Shuaihui, “The Cat's Eye Effect Target Recognition Method Based on Visual Attention,” Chinese Journal of Electronics, vol. 28, no. 5, pp. 1080-1086, 2019, doi: 10.1049/cje.2019.06.027

The Cat's Eye Effect Target Recognition Method Based on Visual Attention

doi: 10.1049/cje.2019.06.027
Funds:  This work is supported by the Hubei Superior and Distinctive Discipline Group of "Mechatronics and Automobiles" (No.XKQ2019031).
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  • Corresponding author: ZHANG Jun (corresponding author) was born in 1985.He received the Ph.D.degree in computer architecture from Institute of Computing Technology,CAS.He is a assistant professor of Hubei University of Arts and Science.His research interests include computer architecture security and machine learning.(Email:zhangjunhbxf@163.com)
  • Received Date: 2018-01-02
  • Rev Recd Date: 2018-06-21
  • Publish Date: 2019-09-10
  • The Cat's eye effect target recognition method based on visual attention (CTRVA) is proposed. The difference image can be processed by a designed second-directional derivative filter at eight directional channels. Morphological method is employed to deal with the filtered image in all directions, which ensures that target can be easily distinguished from background. The salient maps for each channel where the potential targets exist are calculated through the spectral residual approach, and the "target-saliency" map is computed by a designed saliency fusing method. The coarse detection is performed by the adaptive threshold to extract candidate targets from the "target-saliency" map. The real target region is identified by the characteristics of the cat's eye effect target. Experimental results show that the proposed method is efficient and has an outstanding performance for cat's eye effect target detection.
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  • C. L. Ge, et al., "Target classification with cat eye effect", High Power Laser and Partical Beams, Vol.15, No.7, pp.632-634, 2003.
    Y. Zhao, et al., "Three-dimensional analytical formula for oblique and off-axis gaussian beams propagating through a cat's eye optical lens", Chinese Physics Letters, Vol.27, No.3, pp.034101, 2010.
    C. Lecocq, et al., "Sight laser detection modeling", Proc. of the SPIE, Vol.5086, pp.280-286, 2003.
    M. Gong and S. F. He, "Periodicity analysis on cateye reflected beam profiles of optical detectors", Optical Engineering, Vol.56, No.5, pp.053110, 2017.
    D. S. Wu, et al., "Detection of cat-eye effect echo based on unit APD", Proc. of SPIE 10153, Advanced Laser Manufacturing Technology, Vol.101530J, 2016.
    F. Qian, et al., "Fast cat's eye target detection system based on DSP+FPGA architecture," Journal of Optoelectronics. Laser, Vol.27, No.8, pp.863-869, 2016.
    M. H. Liu, Q. S. Chen, X. Y. Li and X. Li, "Comparative study on the numeric models of cat's eye echo power," Laser Journal, Vol.38, No.6, pp.12-15, 2017.
    Y. X. Cai, M. Z. Ouyang and Y. G. Fu, "Research on the mechanism of laser active detection", Laser & Infrarel, Vol.48, No.4, pp.451-4572018.
    D. P. Casasent, et al., "SAR ship detection using new conditional contrast box filter", Proc. of the International Society for Optical Engineering, Vol.3721, pp.274-284, 1999.
    L. Tong, X. Jiang and X. Song, "Target detection based on laser imaging with cat eye effect", Laser & Infrared, Vol.39, pp.982-985, 2009.
    X. Ren and L. Li, "Recognizing cat's eye targets with dual criterions of shape and modulation frequency", Chinese Optics Letters, Vol.9, No.4, pp.041101, 2011.
    L. Li, J. Ren and X. Wang, "Fast cat-eye effect target recognition based on saliency extraction", Optics Communications, Vol.350, No.1, pp.33-39, 2015.
    L. Itti, C. Koch and E. Niebur, "A model of saliency-based visual attention for rapid scene analysis", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.20, No.11, pp.1254-1259, 1998.
    B.C. Ko and J. Nam, "Object-of-interest image segmentation based on human attention and semantic region clustering", J. Opt. Soc.Am. A, Vol.23, No.10, pp.2462-2470, 2006.
    Y. Xu, et al., "Salient target detection based on pseudoWigner-Ville distribution and Rényi entropy", Opt. Lett., Vol.35, No.4, pp.475-477, 2010.
    R. Rensink. "Seeing, sensing, and scrutinizing", Vision Research, Vol.40, No.10-12, pp.1469-1487, 2000.
    D. Walther and C. Koch, "Modeling attention to salient protoobjects", Neural Networks. Vol.19, No.9, pp.1395-1407, 2006.
    D. Walther, L. Itti, M. Riesenhuber, et al., "Attentional selection for object recognition a gentle way", Lecture Notes in Computer Science, Vol.2525, No.1, pp.472-479, 2002.
    R. Haralick, "Digital step edges from zero crossing of second directional derivatives", IEEE Trans. Pattern Anal. Mach. Intell., Vol. PAMI-6, No.1, pp.58-68, 1984.
    X.Q. Luo and X.J. Wu, "A novel fusion detection algorithm for infrared small targets", Proc. of 2009 Third International Conference on Intelligent Information Technology Application, Shanghai, China, pp.427-430, 2009.
    X. Hou and L. Zhang, "Saliency detection:A spectral residual approach", Proc. of 2007 IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, USA, pp.1-8, 2007.
    G. D. Wang and Ch. Y. "Chen and X. B. Shen, Facet-based infrared small target detection method", Electronics Letters, Vol.41 No.22, pp.1244-1246, 2005.
    S. X. Qi, J. Ma and C. Tao, "A robust directional saliencybased method for infrared small-target detection under various complex backgrounds", IEEE Geoscience and Remote Sensing Letters, Vol.10, No.3, pp.495-499, 2012.
    J. Serra, Image Analysis and Mathematical Morphology, Academic Press, New York, USA, 1982.
    Kwon, Der and Nasrabadi, "Adaptive multisensory target detection using feature-based fusion", Opt. Eng. Vo.41, No.1 pp.69-80, 2002.
    R. Achanta, S. Hemami, F. Estrada, et al., "Frequency-tuned salient region detection", Proc. of 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA, pp.1597-1604, 2009.
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