DocumentCode
3582855
Title
Image segmentation based on PCNN model
Author
Zhongyu Tao ; Xiaolong Tang ; Binyu Zhang ; Panshi Tang ; Yue Tan
Author_Institution
Sch. of Comput. Sci. & Eng., Univ. of Electron. & Technol. of China, Chengdu, China
fYear
2014
Firstpage
230
Lastpage
233
Abstract
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.
Keywords
image segmentation; neural nets; PCNN model; adaptive parameters; image processing; image segmentation; network iterations; pulse coupled neural network; Brain modeling; Equations; Firing; Image segmentation; Joining processes; Mathematical model; Neurons; Image segmentation; PCNN; adaptive parameters; iteration numbers;
fLanguage
English
Publisher
ieee
Conference_Titel
Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2014 11th International Computer Conference on
Print_ISBN
978-1-4799-7207-4
Type
conf
DOI
10.1109/ICCWAMTIP.2014.7073397
Filename
7073397
Link To Document