[1]张煜东,吴乐南.基于二维Tsallis熵的改进PCNN图像分割[J].东南大学学报(自然科学版),2008,38(4):579-584.[doi:10.3969/j.issn.1001-0505.2008.04.007]
 Zhang Yudong,Wu Lenan.Image segmentation based on 2D Tsallis entropy with improved pulse coupled neural networks[J].Journal of Southeast University (Natural Science Edition),2008,38(4):579-584.[doi:10.3969/j.issn.1001-0505.2008.04.007]
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基于二维Tsallis熵的改进PCNN图像分割()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
38
期数:
2008年第4期
页码:
579-584
栏目:
信息与通信工程
出版日期:
2008-07-20

文章信息/Info

Title:
Image segmentation based on 2D Tsallis entropy with improved pulse coupled neural networks
作者:
张煜东 吴乐南
东南大学信息科学与工程学院, 南京 210096
Author(s):
Zhang Yudong Wu Lenan
School of Information Science and Engineering, Southeast University, Nanjing 210096, China
关键词:
图像分割 二维直方图 Tsallis熵 脉冲耦合神经网络
Keywords:
image segmentation two-dimensional histogram Tsallis entropy pulse coupled neural network
分类号:
TN911.73
DOI:
10.3969/j.issn.1001-0505.2008.04.007
摘要:
为了改善图像分割的性能, 采用改进的脉冲耦合神经网络(PCNN)进行分割, 通过对其内部活动项进行空不变的单阈值化分割, 来达到对原图像空变阈值化分割效果. 另外分割准则也作了修正, 通过计算图像二维直方图的Tsallis熵, 得到二维Tsallis熵, 以此作为图像分割准则. 最后,修正了动态门限项的下降速度,使得PCNN收敛更快.实验证明二维Tsallis熵准则优于最大Shannon熵准则与最小交叉熵准则, 且改进的PCNN模型比传统PCNN模型收敛更快.
Abstract:
In order to ameliorate traditional image segmentation, an improved pulse coupled neural network(PCNN)is introduced. The inner function item of the PCNN is looked as a new image, which is segmented with space-invariant threshold to achieve the effect that original image is segmented with space-variant threshold. Meanwhile, Tsallis entropy is combined with 2D histogram to engender 2D Tsallis entropy, which is used for guiding image segmentation. Finally, the decrease velocity of dynamic threshold is accelerated in order to make the PCNN converge faster. Experiments show that 2D Tsallis entropy performs better than maximum Shannon entropy and minimum cross entropy, and the improved PCNN can converge more quickly than conventional PCNN.

参考文献/References:

[1] 马义德,戴若兰,李廉,等.生物细胞图像分割技术的进展[J].生物医学工程学杂志,2002,19(3):487-492.
  Ma Yide,Dai Ruolan,Li Lian,et al.The state and development of cell image segmentation technology[J]. J Biomed Eng,2002,19(3):487-492.(in Chinese)
[2] Robert S.The Tsallis entropy of natural information[J]. Physica A:Statistical Mechanics and Its Applications,2007,386(1):101-118.
[3] Muresan Raul C.Pattern recognition using pulse-coupled neural networks and discrete Fourier transforms[J].Neurocomputing,2003,51:487-493.
[4] 曹克非,王参军.Tsallis熵与非广延统计力学[J].云南大学学报:自然科学版,2005,27(6):514-520.
  Cao Kefei,Wang Canjun.Tsallis entropy and nonextensive statistical mechanics[J].Journal of Yunnan University:Natural Science Edition,2005,27(6):514-520.(in Chinese)
[5] Tsallis C,Plastino A R,Zheng W M.Power-law sensitivity to initial conditions—new entropic representation[J]. Chaos Solitons and Fractals,1997,8(6):885-891.
[6] Abutaleb A S.Automatic thresholding of grey level pictures using two dimensional entropy[J].Computer Vision,Graphics and Image Processing,1989,47(1):22-32.
[7] Eckhorn R,Frien A,Bauer R,et al.High frequency oscillations in primary visual cortex of awake monkey[J]. Neuro Rep,1993,4(3):243-246.
[8] Vlatko B.Image object classification using saccadic search,spatio-temporal pattern encoding and self-organisation[J]. Pattern Recognition Letters,2000,21(3):253-263.
[9] Karina W,Thomas L,Vlatko B,et al.Patterns from the sky:satellite image analysis using pulse coupled neural networks for pre-processing,segmentation and edge detection[J].Pattern Recognition Letters,2000,21(3):227-237.
[10] 胡东友,谢振华.基于改进型脉冲耦合神经网络的空间X射线星图分割[J].西安文理学院学报:自然科学版,2007,10(3):21-25.
  Hu Dongyou,Xie Zhenhua.X-ray sky image segmentation using improved pulse coupled neural networks[J].Journal of Xi’an University of Arts and Science:Natural Science Edition,2007,10(3):21-25.(in Chinese)
[11] 熊雪梅,王一鸣,张小超,等.基于脉冲耦合神经网络的蝗虫图像分割[J].农机化研究,2007(1):180-183.
  Xiong Xuemei,Wang Yiming,Zhang Xiaochao,et al.Locust detection by image segmentation based on pulse coupled neural network [J]. Journal of Agricultural Mechanization Research,2007(1):180-183.(in Chinese)
[12] Luan Zhiqiang,Diao Ming,Zhao Zhijiang.Research on fingerprint image segmentation based on pulse coupled neural networks[J].Applied Science and Technology,2006,33(10):25-27.
[13] Stewart Robert D,Fermin Iris,Opper Manfred.Region growing with pulse-coupled neural networks:an alternative to seeded region growing[J]. IEEE Trans Neural Networks,2002,13(6):1557-1662.
[14] 马义德,戴若兰,李廉.一种基于脉冲耦合神经网络和图像熵的自动图像分割方法[J].通信学报,2002,23(1):46-51.
  Ma Yide,Dai Ruolan,Li Lian.Automated image segmentation using pulse neural networks and image entropy[J]. Journal of China Institute of Communications,2002,23(1):46-51.(in Chinese)
[15] Ma Yide,Liu Qing,Qian Zhibai.Automated image segmentation using improved PCNN model based on cross-entropy[C] //Proceedings of 2004International Symposium on Intelligent Multimedia,Video and Speech Processing.Hong Kong,China,2004:743-746.
[16] Yin Pengyeng.Multilevel minimum cross entropy threshold selection based on particle swarm optimization[J].Applied Mathematics and Computation,2007,184(2):503-513.
[17] Hler R A.Segmentation system based on thresholding[J].Computer Vision,Graphics and Image Processing,1981,15(6):319-324.

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备注/Memo

备注/Memo:
作者简介: 张煜东(1985—), 男,博士生; 吴乐南(联系人), 男, 博士,教授, 博士生导师,wuln@seu.edu.cn.
基金项目: 高等学校科技创新工程重大项目培育资金资助项目(706028)、江苏省自然科学基金资助项目(BK2007103).
引文格式: 张煜东, 吴乐南.基于二维Tsallis熵的改进PCNN图像分割[J].东南大学学报:自然科学版,2008,38(4):579-584.
更新日期/Last Update: 2008-07-20