Moving object detection in a sequence of images taken from non-stationary camera

Abstract

Moving object detection is a vital aspect of motion analysis. It has drawn an increasing attention in the recent years due to its applications such as in communication, traffic monitoring, security surveillance, robot navigation and servoing. Despite the fact that much research efforts have been devoted to this area, detecting moving object using non-stationary moving camera remains a great challenge. The research undertaken in this thesis is mainly concentrated on developing a reliable and robust detection system which incorporates some operation on images such as thresholding, blob labelling, blob matching, filtering and blob analysis. The basic idea behind this system is that the motion of the moving object is different with the motion of background object. Path transversed within a certain period of observation of the moving object is usually longer than background object. By using blob labelling and blob matching operation, this system would be able to track binary blobs over an arbitarily long image sequence. The criteria for matching binary blobs from two adjacent frames are position, height, width, area, colour and aspect ratio. If the the path transversed of a binary blob within a certain period of observation is sufficiently long, then the tracked blob is considered as moving object