Article ID Journal Published Year Pages File Type
1784690 Infrared Physics & Technology 2010 7 Pages PDF
Abstract

A novel and robust pedestrian detection method in thermal infrared images based on the double-density dual-tree complex wavelet transform (DD-DT CWT) and wavelet entropy is presented in this paper. The regions of interest (ROIs) are located first making use of high brightness property of the pedestrian pixels caused by the self-emission of the pedestrians related to the Planck’s law. The candidate ROIs are then decomposed by DD-DT CWT and the wavelet entropy features are extracted from the high frequency subbands. The true pedestrian regions are finally classified and recognized using the support vector machine (SVM) classifier. Comparisons between our approach and traditional approaches are presented and experimental results using several thermal infrared image databases show the proposed scheme to be very promising.

Related Topics
Physical Sciences and Engineering Physics and Astronomy Atomic and Molecular Physics, and Optics
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