Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Objects Based Change Detection in a Pair of Gray-Level Images
 

Summary: Objects Based Change Detection in a Pair of
Gray-Level Images
OFER MILLER*
, ARIE PIKAZ, AMIR AVERBUCH
School of Computer Science
Tel-Aviv University, Tel-Aviv 69978, Israel
E-mail*
: millero@post.tau.ac.il Fax number: 972-3-6409357
Abstract
The goal of the presented change detection algorithm is to extract objects that appear in
only one of two input images. A typical application is surveillance, where a scene is
captured at different times of the day or even on different days. In this paper we assume that
there may be a significant noise or illumination differences between the input images. For
example, one image may be captured in daylight while the other was captured during night
with an infrared device. By using a connectivity analysis along gray-levels technique, we
extract significant blobs from both images. All the extracted blobs are candidates to be
classified as changes or part of a change. Then, the candidate blobs from both images are
matched. A blob from one image that does not satisfy the matching criteria with its
corresponding blob from the other image is considered as an object of change. The
algorithm was found to be reliable, fast, accurate, and robust even under extreme changes in

  

Source: Averbuch, Amir - School of Computer Science, Tel Aviv University

 

Collections: Computer Technologies and Information Sciences