Unsupervised automatic change detection in images under time-varying illumination
N. D. Atkekar, Sayeed Ahmed Khan, M.A. Joshi · 2008
It is not surprising that the process of change detection is fundamental to many machine vision applications. Most change detection algorithms assume that the illumination on a scene will remain constant. Unfortunately, this assumption is not necessarily valid outside a well-controlled laboratory setting. The accuracy of existing algorithms decreases significantly when faced up with image sequences in which the illumination is allowed to vary. In this paper an unsupervised change detection algorithm has been proposed, it performs the change detection without any additional information besides the raw images considered. It performs well under time-varying illumination conditions, where other algorithms fail to perform