Human detection using OT-MACH filter in cluttered FLIR imagery

An improvement to the Optimal Trade-off Maximum Average Correlation Height (OT-MACH) filter with the addition of a Rayleigh distribution filter has been used to detect humans in FLIR imagery scenes. The Rayleigh distribution filter is applied to the OT-MACH filter to provide a sharper low frequency cut-off which improves the OT-MACH filter performance in terms of target discrimination. The OT-MACH filter has been trained using a Computer Aided Design (CAD) model and tested on the corresponding real target object in high clutter environments acquired from a Forward Looking Infra Red (FLIR) sensor. Evaluation of the performance of the Rayleigh modified OT-MACH filter is reported for the recognition of humans present within the thermal infra-red image data set.