Title :
Automatic Target Detection and Tracking in FLIR Image Sequences Using Morphological Connected Operator
Author :
Chang´an Wei ; Shouda Jiang
Author_Institution :
Autom. Test & Control Inst., Harbin Inst. of Technol., Harbin
Abstract :
In this paper, we propose a method for detecting and tracking small targets in forward looking infrared (FLIR) image sequences taken from an airborne moving platform. Firstly, we adopt the morphological connected operator to remove the undesirable clutter in the background. Secondly, the image is decomposed by morphological Haar wavelet, and the wavelet energy image is computed from the horizontal and vertical detail images, and it is fused with the scaled image. Thirdly, the targets are extracted coarse-to-fine by adaptive double thresholding. Finally, targets are modeled by intensity probabilistic density function and tracked using mean shift algorithm. The experiments performed on the AMCOM FLIR data set verify the validity and robustness of the algorithm.
Keywords :
Haar transforms; image sequences; infrared imaging; object detection; target tracking; wavelet transforms; Haar wavelet; adaptive double thresholding; airborne moving platform; automatic target detection; forward looking infrared image sequences; morphological connected operator; probabilistic density function; target tracking; Gray-scale; Image edge detection; Image processing; Image reconstruction; Image sequences; Infrared detectors; Object detection; Signal processing algorithms; Signal to noise ratio; Target tracking;
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing, 2008. IIHMSP '08 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-0-7695-3278-3
DOI :
10.1109/IIH-MSP.2008.193