Open Access

Real-Time Multiple Moving Targets Detection from Airborne IR Imagery by Dynamic Gabor Filter and Dynamic Gaussian Detector

EURASIP Journal on Image and Video Processing20102010:124681

https://doi.org/10.1155/2010/124681

Received: 1 February 2010

Accepted: 29 June 2010

Published: 18 July 2010

Abstract

This paper presents a robust approach to detect multiple moving targets from aerial infrared (IR) image sequences. The proposed novel method is based on dynamic Gabor filter and dynamic Gaussian detector. First, the motion induced by the airborne platform is modeled by parametric affine transformation and the IR video is stabilized by eliminating the background motion. A set of feature points are extracted and they are categorized into inliers and outliers. The inliers are used to estimate affine transformation parameters, and the outliers are used to localize moving targets. Then, a dynamic Gabor filter is employed to enhance the difference images for more accurate detection and localization of moving targets. The Gabor filter's orientation is dynamically changed according to the orientation of optical flows. Next, the specular highlights generated by the dynamic Gabor filter are detected. The outliers and specular highlights are fused to indentify the moving targets. If a specular highlight lies in an outlier cluster, it corresponds to a target; otherwise, the dynamic Gaussian detector is employed to determine whether the specular highlight corresponds to a target. The detection speed is approximate 2 frames per second, which meets the real-time requirement of many target tracking systems.

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Authors’ Affiliations

(1)
Department of Computer Science, College of Engineering, Technology and Computer Science, Tennessee State University
(2)
Department of Electrical and Computer Engineering, Tennessee State University

Copyright

© Fenghui Yao et al. 2010

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.