Adaptive Change Detection

In this paper we propose a method to detect meaningful changes between two images. By meaningful changes we refer to those due to variations in the visual content of the images, rejecting illumination changes as non-meaningful. The method has been devised in order to assure a low number of wrong detections and it depends on a few parameters. These parameters can be tuned once and for all for any input images, which makes the method virtually automatic.

[1]  Paul C. Smits,et al.  Toward specification-driven change detection , 2000, IEEE Trans. Geosci. Remote. Sens..

[2]  Jean-Michel Morel,et al.  From Gestalt Theory to Image Analysis: A Probabilistic Approach , 2007 .

[3]  Lionel Moisan,et al.  A Grouping Principle and Four Applications , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Lionel Moisan,et al.  On the Theory of Planar Shape , 2003, Multiscale Model. Simul..

[5]  Paul L. Rosin Thresholding for change detection , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[6]  Julie Delon Midway Image Equalization , 2004, Journal of Mathematical Imaging and Vision.

[7]  Pascal Monasse,et al.  Contrast invariant registration of images , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[8]  Badrinath Roysam,et al.  Image change detection algorithms: a systematic survey , 2005, IEEE Transactions on Image Processing.

[9]  Til Aach,et al.  Bayesian algorithms for adaptive change detection in image sequences using Markov random fields , 1995, Signal Process. Image Commun..

[10]  Til Aach,et al.  Statistical model-based change detection in moving video , 1993, Signal Process..