Title :
Design method for CNN Gabor-type filters
Author_Institution :
Fac. of Electron. & Telecommun., Tech. Univ. of Iasi, Iasi
fDate :
Aug. 31 2008-Sept. 3 2008
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;
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
DOI :
10.1109/ICECS.2008.4674855
