Intrusion detection robust to slow and abrupt lighting changes

In this communication we present an image based object detection algorithm which is applied to intrusion detection. The algorithm is based on the comparison of input edges and temporally filtered edges of the background. It is characterized by very low computational and memory loads, high sensitivity to the presence of physical intruders and high robustness to slow and abrupt lighting changes. The algorithm is implementable on a cheap digital signal processor. It was tested on a data base of about one thousand gray-level CIF-format frames representing static scenes with various contents (light sources, intruders, lighting changes), and neither false alarm nor detection failure occurred. The number of parameters involved by the algorithm is very low, and their values do not require a fine tuning. The same set of parameters performs equally well in different conditions: different scenes, various lighting changes, various object sizes.