IMAGE SEGMENTATION BASED ON PCNN MODEL

被引：0
|
作者：
Tao, Zhongyu [1 ]
Tang, Xiaolong [1 ]
Zhang, Binyu [2 ]
Tang, Panshi [1 ]
Tan, Yue [1 ]
机构：
[1] Univ Elect & Technol China, Sch Comp Sci & Engn, Chengdu 611731, Peoples R China
[2] Hefei Normal Univ, Sch Chem & Chem Engn, Hefei 230601, Peoples R China
来源：
2014 11TH INTERNATIONAL COMPUTER CONFERENCE ON WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING (ICCWAMTIP) | 2014年
关键词：
Image segmentation; PCNN; adaptive parameters; iteration numbers;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Image segmentation is very important in image processing which can segment the images into the different parts, thus, we can focus on the parts in which we are interested. Recent years, there are many models using for the image segmentation, Pulse Coupled Neural Networks model is very popular model which is widely used among many models. Although, PCNN models needs trivial adaptive parameters and network iterations to set, but it has the advantages, such as rotation invariance, intensity invariance, scale invariance, etc. Above advantages make PCNN is very suitable for image segmentation.
引用
收藏
页码：230 / 233
页数：4
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