A new, simple, fast and effective method for moving object detection in outdoor environments, invariant to extreme illumination changes is presented as an improvement to the shading model method described in. It is based on an analytical parameter introduced in the shading model, background updating technique and window processing. | Yugoslav Journal of Operations Research 14 (2004), Number 1, 117-132 NEW ALGORITHM FOR MOVING OBJECT DETECTION Vesna ZELJKOVIĆ, Željen TRPOVSKI, Vojin ŠENK Faculty of Technical Sciences, University of Novi Sad Novi Sad, Serbia and Montenegro vecko@ Received: November 2002 / Accepted: July 2003 Abstract: A new, simple, fast and effective method for moving object detection in outdoor environments, invariant to extreme illumination changes is presented as an improvement to the shading model method described in [8]. It is based on an analytical parameter introduced in the shading model, background updating technique and window processing. Keywords: Moving object, detection, illumination. 1. INTRODUCTION In recent years extensive investigations and analyses have been done in the domain of moving object detection. Detection of moving objects in video processing plays a very important role in many vision applications. The vision systems that include image processing methods are widely implemented in many areas as traffic control [5]-[7], video surveillance of unattended outdoor environments [3], video surveillance of objects [1], etc. The change detection algorithms implemented in these video systems provide low-level information that can be used by higher level algorithms to determine the information desired (the trajectory of an object, the control of traffic flow, etc). Methods for moving object detection must be accurate and robust so that complex video systems can operate successfully. Most of the existing algorithms for moving object detection assume that the illumination in a scene remains constant. Unfortunately, this assumption is not valid, especially in outdoor environment. The efficiency of some of existing techniques diminishes significantly if the illumination varies. There are two types of methods that realize moving object detection. One detects changes at pixel level and the other is based on feature comparison. The first method is better .
