DocumentCode
3382243
Title
Design method for CNN Gabor-type filters
Author
Matei, Radu
Author_Institution
Fac. of Electron. & Telecommun., Tech. Univ. of Iasi, Iasi
fYear
2008
fDate
Aug. 31 2008-Sept. 3 2008
Firstpage
320
Lastpage
323
Abstract
A class of widely used tools for image processing and computer vision applications are Gabor filters. In this paper analog implementation of these filters using cellular neural networks is approached. Some template design methods for Gabor filters are proposed, based on rational approximations of the frequency response, and their accuracy and efficiency is discussed comparatively.
Keywords
Gabor filters; approximation theory; cellular neural nets; computer vision; frequency response; network synthesis; CNN Gabor filters; cellular neural networks; computer vision; frequency response; image processing; Cellular neural networks; Design methodology; Feature extraction; Filtering; Frequency response; Gabor filters; Image processing; Motion analysis; Nonlinear filters; Transfer functions;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronics, Circuits and Systems, 2008. ICECS 2008. 15th IEEE International Conference on
Conference_Location
St. Julien´s
Print_ISBN
978-1-4244-2181-7
Electronic_ISBN
978-1-4244-2182-4
Type
conf
DOI
10.1109/ICECS.2008.4674855
Filename
4674855
Link To Document