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

Fast detection of small infrared objects in maritime scenes using local minimum patterns

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

4 Author(s)
Baojun Qi ; Inst. of Autom., Nat. Univ. of Defense Technol., Changsha, China ; Tao Wu ; Bin Dai ; Hangen He

This paper describes a novel approach for fast detecting small maritime objects in infrared (IR) images. It is based on the local minimum patterns (LMP), which are theoretically the approximations of some stationary wavelet transforms (SWT). Using LMP to estimate the background with a single image, we obtain an object-aware saliency map by background subtraction. Regions of potential objects are then segmented by an adaptive threshold based on the histogram of the saliency map. We finally propose a fast clustering algorithm for localizing objects from segmented regions. Extensive experiments on challenging data sets show a competitive performance.

Published in:

Image Processing (ICIP), 2011 18th IEEE International Conference on

Date of Conference:

11-14 Sept. 2011

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.