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Weight adaptation and oscillatory correlation for image segmentation
Chen, K ; Wang, DL ; Liu, XW
刊名ieee神经网络汇刊
2000
关键词desynchronization image segmentation LEGION nonlinear smoothing oscillatory correlation synchronization weight adaptation PERCEPTUAL ORGANIZATION EDGE-DETECTION ANISOTROPIC DIFFUSION NEURAL OSCILLATORS REGION INFORMATION COMPETITION ALGORITHM NETWORKS
DOI10.1109/72.870043
英文摘要We propose a method for image segmentation based on a neural oscillator network, Unlike previous methods, weight adaptation is adopted during segmentation to remove noise and preserve significant discontinuities in an image. Moreover, a logarithmic grouping rule is proposed to facilitate grouping of oscillators representing pixels with coherent properties. We show that weight adaptation plays the roles of noise removal and feature preservation. In particular, our weight adaptation scheme is insensitive to termination time and the resulting dynamic weights in a wide range of iterations lead to the same segmentation results. A computer algorithm derived from oscillatory dynamics is applied to synthetic and real images and simulation results show that the algorithm yields favorable segmentation results in comparison with other recent algorithms. In addition, the weight adaptation scheme can be directly transformed to a novel feature-preserving smoothing procedure: We also demonstrate that our nonlinear smoothing algorithm achieves good results for various kinds of images.; Computer Science, Artificial Intelligence; Computer Science, Hardware & Architecture; Computer Science, Theory & Methods; Engineering, Electrical & Electronic; SCI(E); EI; 50; ARTICLE; 5; 1106-1123; 11
语种英语
内容类型期刊论文
源URL[http://ir.pku.edu.cn/handle/20.500.11897/152129]  
专题信息科学技术学院
推荐引用方式
GB/T 7714
Chen, K,Wang, DL,Liu, XW. Weight adaptation and oscillatory correlation for image segmentation[J]. ieee神经网络汇刊,2000.
APA Chen, K,Wang, DL,&Liu, XW.(2000).Weight adaptation and oscillatory correlation for image segmentation.ieee神经网络汇刊.
MLA Chen, K,et al."Weight adaptation and oscillatory correlation for image segmentation".ieee神经网络汇刊 (2000).
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