Cart (Loading....) | Create Account
Close category search window
 

GPU implemention of fast Gabor filters

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
XinXin Wang ; Dept. of Electron. & Comput. Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China ; Shi, B.E.

With their parallel multi-core architecture, Programmable Graphics Processing Units (GPUs) are well suited for implementing biologically-inspired visual processing algorithms, such as Gabor filtering. We compare several GPU implementations of Gabor filtering. On the same graphics card (an NVIDIA GeForce 9800 GTX+) and for convolution kernel radii from 8 to 48 pixels, an algorithm that decomposes Gabor filtering into a number of simpler steps results in an algorithm that is 2.2 to 33 times faster than direct 2D convolution and 2.8 to 6.6 times faster than a FFT based approach. Surprisingly, in comparison with an optimized algorithm for Gabor filtering running on a PC (Core2 Duo 3.16GHz), it is only 4-10 times faster. The PC can efficiently implement a recursive 1D filter, which requires far fewer arithmetic operations than convolution. However, due to data dependencies, this recursive filter typically runs slower than 1D convolution on the GPU. This highlights the importance of simultaneously considering both arithmetic and memory operations in porting algorithms to GPUs.

Published in:

Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on

Date of Conference:

May 30 2010-June 2 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.