GPGPU real-time texture analysis framework

M. A. Akhloufi; F. Gariepy; G. Champagne

doi:10.1117/12.871082

25 January 2011 GPGPU real-time texture analysis framework

M. A. Akhloufi, F. Gariepy, G. Champagne

Proceedings Volume 7872, Parallel Processing for Imaging Applications; 787208 (2011) https://doi.org/10.1117/12.871082
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

This work presents a framework for fast texture analysis in computer vision. The speedup is obtained using General- Purpose Processing on Graphics Processing Units (GPGPU technology). For this purpose, we have selected the following texture analysis techniques: LBP (Local Binary Patterns), LTP (Local Ternary Patterns), Laws texture kernels and Gabor filters. GPU optimizations are compared to CPU optimizations using MMX-SSE technologies and Multicore parallel programming. The experimental results show an important increase in the performance of the proposed algorithms when GPGPU is used particularly for large image sizes.

Citation Download Citation

M. A. Akhloufi, F. Gariepy, and G. Champagne "GPGPU real-time texture analysis framework", Proc. SPIE 7872, Parallel Processing for Imaging Applications, 787208 (25 January 2011); https://doi.org/10.1117/12.871082

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available