By Topic

Computing image texture features in parallel computers

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

1 Author(s)
Sanz, J.L.C. ; IBM Almaden Res. Center, San Jose, CA, USA

The problem of computing image texture features in parallel computers is addressed. It is shown that R. Haralick's texture measures (1973) are amenable to efficient implementation in certain fine-grained architectures. The main operation used to compute these features is the SEND, also called Random Access Write, command. This command is efficiently implemented in a number of computers, such as binary n -cubes, mesh-arrays, and some shared-memory systems. It is shown that the computation of gray-level dependency matrices requires random global communication patterns. This feature and the need for other standard local processing make the classification measures proposed by Haralick and his associates good candidates as benchmarks for parallel computer vision architectures

Published in:

Proceedings of the IEEE  (Volume:76 ,  Issue: 3 )