Robust and efficient change detection algorithm

0Citations
Citations of this article
1Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Change detection in temporally related image sequences is a primary tool for extraction and detection of activities in background scene with vast and wide range of applications ranging from security and surveillance to fault detection and power savings. The prevalent methods for change detection are derived from the difference extraction where differences in the gray-level of values of the pixels between the two or more image sequences are used for the estimation and prediction of these changes. However this approach and its derived modifications are largely dependent and reliant on the application of value thresholds to provide significance to the differences, in order to compensate for the vulnerability of these methods to illumination variability and noise. A frequency domain approach to change detection is proposed that eliminates the need for thresholds and provides comparatively superior performance to the existing algorithms. © 2010 Springer-Verlag.

Cite

CITATION STYLE

APA

Yu, F., Chukwu, M., & Jonathan Wu, Q. M. (2010). Robust and efficient change detection algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6335 LNCS, pp. 338–344). https://doi.org/10.1007/978-3-642-15470-6_35

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free