Automatic Target Recognition and Tracking in Forward-Looking Infrared Image Sequences with a Complex Background

作者：Yoon Seok Pil; Song Taek Lyul; Kim Tae Han^*

来源：International Journal of Control Automation and Systems, 2013, 11(1): 21-32.

DOI：10.1007/s12555-011-0226-z

• Automatic target recognition
• Bayesian classifier
• JDC-JIHPDAF
• NMI features

This paper presents a technique for automatic airborne target recognition and tracking in forward-looking infrared (FLIR) images with a complex background. An image splitting and merging method is applied for detecting target signals. The presence of a complex background due to clouds and sun glint generates clutter in the image with the resulting possibility of false alarms. A Bayesian classifier trained using the NMI (normalized moment of inertia) feature is proposed for efficient clutter rejection. After classification, target candidates are entered into a tracking filter. As an efficient and robust multi-target tracking filter in cluttered environments, the JDC-JIHPDAF is proposed. Experimental results using a wide range of real FLIR images ensure reliable classification and automatic target recognition performance.

• 出版日期2013-2