DENG Xiangyu and MA Yide, “PCNN Model Analysis and Its Automatic Parameters Determination in Image Segmentation and Edge Detection,” Chinese Journal of Electronics, vol. 23, no. 1, pp. 97-103, 2014,
Citation: DENG Xiangyu and MA Yide, “PCNN Model Analysis and Its Automatic Parameters Determination in Image Segmentation and Edge Detection,” Chinese Journal of Electronics, vol. 23, no. 1, pp. 97-103, 2014,

PCNN Model Analysis and Its Automatic Parameters Determination in Image Segmentation and Edge Detection

Funds:  This work is supported by the National Natural Science Foundation of China (No.61175012), the Specialized Research Fund for the Doctoral Program of Higher Education of China (No.20110211110026), and the Education Department Graduate Tutor Project of Gansu, China (No.1014-02).
  • Received Date: 2012-03-01
  • Rev Recd Date: 2013-01-01
  • Publish Date: 2014-01-05
  • The Pulse coupled neural network (PCNN) has been widely used in digital image processing, but the automatic parameters determination is still a difficult aspect, which becomes the focus of PCNN research. In this paper, by the classical solution to difference equations and the time-domain analysis of PCNN model, we provide the expressions of the firing time and the firing period of neurons, and reveal the "mathematics firing" phenomenon of PCNN. Based on this, we propose a new method of automatic parameters determination based on both eliminating the "mathematics firing" and getting the highest efficiency of PCNN. We also present an edge detection model on the basis of image segmentation of PCNN and a method to determine automatically the parameters of the model. Experimental results prove the validity and efficiency of our proposed algorithm for the segmentation and the edge detection of the test images.
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  • R. Eckhorn, H.J. Reitboeck, M. Arndt, P. Dicke,"Feature linking via synchronization among distributed assemblies: SimulaFig. 10. Comparison with other algorithms: (a) Segmentation result of the traditional parameters; (b) Result of Sobel method; (c) Result of Laplacian of Gaussian methodl; (d) Result of Canny method tion of results from cat visual cortex", Neural Computation, Vol.2, No.3, pp293-307, 1990.
    J.L. Johnson, M.L. Padgett,"PCNN models and applications", IEEE Transactions on Neural Networks, Vol.10, No.3, pp480498, 1999.
    Shuo Wei, Qu Hong, Mengshu Hou,"Automatic image segmentation based on PCNN with adaptive threshold time constant", Neurocomputing, Vol.74, No.9, pp.1485-1491, 2011.
    G. Kuntimad, H.S. Ranganath,"Perfect image segmentation using pulse-coupled neural networks", IEEE Transactions on Neural Networks, Vol.10, No.3, pp.591-598, 1999.
    Yu Jiangbo, Chen Houjin, Wang Wei, Li Jupeng,"Parameter determination of pulse coupled neural network in image processing", Acta Electronica Sinica, Vol.36, No.1, pp.81-85, 2008. (in Chinese)
    Min Li, Wei Cai, Zheng Tan,"Adaptive parameters determination method of pulse coupled neural network based on water valley area", I. King et al. (Eds.): ICONIP 2006, Part II, LNCS 4233, pp.713-720, 2006.
    Yide Ma, Rolan Dai, Lian Li and LinWei,"Image segmentation of embryonic plant cell using pulse-coupled neural networks", Chinese Science Bulletin, Vol.47, No.02, pp.169-173, 2002.
    Yuli Chen, Sung-Kee Park, Yide Ma,"A new automatic parameter setting method of a simplified PCNN for image segmentation", IEEE Transactions on Neural Networks, Vol.22, No.6, pp.880-892, 2011.
    Yang Zhiyong, Zhou Qiyun, Zhou Dingkang,"Gray image edge detection method based on PCNN", Computer Engineering Applications, Vol.40, No.4, pp.92-94, 2004. (in Chinese)
    Liang Zhou, Yu Sun, Jianguo Zheng,"Automated color image edge detection using improved PCNN model", WSEAS Transactions on Computers, Vol.17, No.4, pp.184-189, 2008.
    M. Yonekawa and H. Kurokawa,"An automatic parameter adjustment method of pulse coupled neural network for image segmentation", in Proc. Artif. Neural Netw., Limassol, Cyprus, pp.834-843, 2009.
    Y.W. Bi, T.S. Qiu, X.B. Li and Y. Guo,"Automatic image segmentation based on a simplified pulse coupled neural network", Lecture Notes in Computer Science, Vol.3174, pp.405410, 2004.
    Deng Xiang-yu, Ma Yi-de,"PCNN model automatic parameters determination and its modified model", Acta Electronica Sinica, Vol.40, No.(5), pp.955-964, 2012. (in Chinese)
    G.T. Fechner, Elemente der psychophysik. Leipzig, Germany: Breitkopf & Hartel, 1860.
    R.P. Broussard, S.K. Rogers, M.E. Oxley, et al.,"Physiologically motivated image fusion for object detection using a pulse coupled neural network", IEEE Transactions on Neural Networks, Vol.10, No.3, pp.554-563, 1999.
    H.S. Ranganath, G.J. Kuntimad, L. Johnson,"Pulse coupled neural networks for image processing", IEEE Southeastcon, Raleigh, NC, pp.37-43, 1995.
    H.S. Ranganath, G. Kuntimad,"Object detection using pulse coupled neural networks", IEEE Transactions on Neural Networks, Vol.10, No.3, pp.615-620, 1999.
    Gu Xiaodong, Guo Shide, Yu Daoheng,"A new approach for image edge detection using PCNN", Computer Engineering Applications, Vol.39, No.16, pp.1-2, 55, 2003. (in Chinese)
    Kang Chung-chia, Wang Wen-june,"A novel edge detection method based on the maximizing objective function", Pattern Recognition, Vol.40, No.2, pp.609-618, 2007.
    Bao Qingfeng, Wang Jicheng,"A new color image segmentation based on PCNN", Computer Engineering and Applications, No.27, pp.48-50, 2005. (in Chinese)
    J.L. John, D. Ritter,"Observation of periodic waves in a pulsecoupled neural network", Opt. Lett, Vol.18, No.15, pp.12531255, 1993.
    Ma Yide, Su Maojun, Chen Rui,"Image binarization based on PCNN and corresponding segmentation evaluation method", Journal of South China University of Technology, Vol.5, No.37, pp.49-53, 2009. (in Chinese)
    K. Chen, D.L. Wang,"A dynamically coupled neural oscillator network for image segmentation", Neural Netw., Vol.15, No.3, pp.423-439, 2002.
    H. Berg, R. Olsson, T. Lindblad, J. Chilo,"Automatic design of pulse coupled neurons for image segmentation", Neurocomputing, Vol.71, No.10, pp.1980-1993, 2008.
    J. Schreiter, J. Döge, D. Matolin, R. Schüffny, A. Heittmann, U. Ramacher,"Image segmentation by a PCNN with adaptive weights", Proceeding (396) Visualization, Imaging, and Image Processing, Benalmádena, Spain, pp.396-802, 2003.
    J.A. Karvonen,"Baltic sea ice SAR segmentation and classification using modified pulse-coupled neural networks", IEEE Trans. Geosci. Remote Sensing, Vol.42, No.7, pp.1566-1574, 2004.
    Li Zhiqiang, Cheng Feiyan, An Lizhe, Ma Yide, et al.,"Edge detection of color images based on the improved multi-dimensional PCNN", Journal of Lanzhou University (Natural Sciences), Vol.45, No.5, pp.130-134, 2009. (in Chinese)
    Y. Lu, J. Miao, L. Duan, Y. Qiao and R. Jia,"A new approach to image segmentation based on simplified region growing PCNN", Appl. Math. Comput., Vol.205, No.2, pp.807-814, 2008.
    Tan Yingfang, Zhou Dongming, Zhao Dongfeng, et al.,"Color image segmentation and edge detection using unit-linking PCNN image entropy", Computer Engineering and Applications, Vol.45, No.12, pp.174-177, 2009. (in Chinese)
    Z. Wang, Y. Ma, F. Cheng and L. Yang,"Review of pulsecoupled neural networks", Image Vis. Comput., Vol.28, No.1, pp.5-13, 2010.
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      沈阳化工大学材料科学与工程学院 沈阳 110142

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