DocumentCode
1591293
Title
Image Segmentation by Using Discrete Tchebichef Moments and Quantum Neural Network
Author
Liu, Zhen ; Bai, Zhongying ; Shi, Jinming ; Chen, Hao
Author_Institution
Beijing Univ. of Posts & Telecommun., Beijing
Volume
3
fYear
2007
Firstpage
137
Lastpage
140
Abstract
A new image segmentation method based on discrete Tchebichef moments and quantum neural networks is presented. The Tchebichef moments in certain local window of each pixel in the image are computed and input to quantum neural network . Quantum neural networks , which use multilevel transfer function, have the inherent fuzzy characteristics. The point accommodates to the connatural uncertainty of fractional image data in image segmentation procession. Experiments confirm that the performance of our proposed method is more accurate and has less iterative times in comparison with the traditional segmentation methods based on Legendre moments and BP neutral networks.
Keywords
backpropagation; fuzzy set theory; image segmentation; neural nets; quantum computing; transfer functions; BP neutral networks; Legendre moments; discrete Tchebichef moments; discrete image segmentation method; fractional image data; multilevel transfer function; quantum neural network; Artificial satellites; Fuzzy neural networks; Image segmentation; Meteorology; Neural networks; Pixel; Polynomials; Quantum computing; Quantum mechanics; Transfer functions;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2875-5
Type
conf
DOI
10.1109/ICNC.2007.431
Filename
4344493
Link To Document