Human detection in sensitive security areas through recognition of omega shapes using MACH filters
Saad Ur Rehman, Farhan Riaz, Ali Hassan, Muwahida Liaquat, Rupert C. D. Young · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
Human detection has gained considerable importance in aggravated security scenarios over recent times. An effective security application relies strongly on detailed information regarding the scene under consideration. A larger accumulation of humans than the number of personal authorized to visit a security controlled area must be effectively detected, amicably alarmed and immediately monitored. A framework involving a novel combination of some existing techniques allows an immediate detection of an undesirable crowd in a region under observation. Frame differencing provides a clear visibility of moving objects while highlighting those objects in each frame acquired by a real time camera. Training of a correlation pattern recognition based filter on desired shapes such as elliptical representations of human faces (variants of an Omega Shape) yields correct detections. The inherent ability of correlation pattern recognition filters caters for angular rotations in the target object and renders decision regarding the existence of the number of persons exceeding an allowed figure in the monitored area.