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

Time complexity of traditional vision algorithms on a block-based image processor (BLIP)

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

6 Author(s)

Generally, image processing algorithms are suitable for parallel execution. However, this has not yet been exploited in a feasible design. Instead of the common practice, where the pixels on the sensor and the processor arrays are mapped onto each other, we propose the idea to split the image into multiple blocks of pixels (of the same size) and map each of these blocks onto one processing element. This decreases the hardware consumption and the communication overhead between the processing elements. This paper describes the architecture of the processor (the block-based image processor, BLIP) and the feasibility of low-, mid- and high-level image processing algorithms on the proposed architecture.

Published in:

Distributed Smart Cameras (ICDSC), 2012 Sixth International Conference on

Date of Conference:

Oct. 30 2012-Nov. 2 2012

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.