Automatic design of pulse coupled neurons for image segmentation

被引:32
作者
Berg, Henrik [1 ]
Olsson, Roland [1 ]
Lindblad, Thomas [2 ]
Chilo, Jose [3 ]
机构
[1] Ostfold Univ Coll, Fac Comp Sci, N-1757 Halden, Norway
[2] Royal Inst Technol, Dept Phys, S-10961 Stockholm, Sweden
[3] Univ Gavle, S-80176 Gavle, Sweden
关键词
image segmentation; pulse coupled neural networks; automatic programming; ADATE;
D O I
10.1016/j.neucom.2007.10.018
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Automatic Design of Algorithms through Evolution (ADATE) is a program synthesis system that creates recursive programs in a functional language with automatic invention of recursive help functions and self-adaptive optimization of numerical values. We implement a neuron in a pulse coupled neural network (PCNN) as a recursive function in the ADATE language and then use ADATE to automatically evolve better PCNN neurons for image segmentation. Our technique is generally applicable for automatic improvement of most image processing algorithms and neural computing methods. It may be used either to generally improve a given implementation or to tailor that implementation to a specific problem, which with respect to image segmentation for example can be road following for autonomous vehicles or infrared image segmentation for heat seeking missiles that are to distinguish the heat source of the target from flares. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:1980 / 1993
页数:14
相关论文
共 30 条
  • [1] [Anonymous], INT C NEUR NETW SAN
  • [2] [Anonymous], 1998, IMAGE PROCESSING USI
  • [3] ADAPTIVE IMAGE SEGMENTATION USING A GENETIC ALGORITHM
    BHANU, B
    LEE, S
    MING, J
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1995, 25 (12): : 1543 - 1567
  • [4] Adaptive integrated image segmentation and object recognition
    Bhanu, B
    Peng, J
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 2000, 30 (04): : 427 - 441
  • [5] An adaptive neuro-fuzzy system for automatic image segmentation and edge detection
    Boskovitz, V
    Guterman, H
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2002, 10 (02) : 247 - 262
  • [6] Supervised tensor learning
    Dacheng Tao
    Xuelong Li
    Xindong Wu
    Weiming Hu
    Stephen J. Maybank
    [J]. KNOWLEDGE AND INFORMATION SYSTEMS, 2007, 13 (01) : 1 - 42
  • [7] Feature Linking via Synchronization among Distributed Assemblies: Simulations of Results from Cat Visual Cortex
    Eckhorn, R.
    Reitboeck, H. J.
    Arndt, M.
    Dicke, P.
    [J]. NEURAL COMPUTATION, 1990, 2 (03) : 293 - 307
  • [8] Efficient graph-based image segmentation
    Felzenszwalb, PF
    Huttenlocher, DP
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 2004, 59 (02) : 167 - 181
  • [9] GEARD N, 2002, P 2002 C EV COMP
  • [10] Gonzalez Rafael C, 2002, DIGITAL IMAGE PROCES