Hybrid multi-resolution detection of moving targets in infrared imagery

Tewary, Suman and Akula, Aparna and Ghosh, Ripul and Kumar, Satish and Sardana, H.K. (2014) Hybrid multi-resolution detection of moving targets in infrared imagery. Infrared Physics & Technology, 67. pp. 173-183. ISSN 1350-4495

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Official URL: http://www.sciencedirect.com/science/article/pii/S...

Abstract

A hybrid moving target detection approach in multi-resolution framework for thermal infrared imagery is presented. Background subtraction and optical flow methods are widely used to detect moving targets. However, each method has some pros and cons which limits the performance. Conventional background subtraction is affected by dynamic noise and partial extraction of targets. Fast independent component analysis based background subtraction is efficient for target detection in infrared image sequences; however the noise increases for small targets. Well known motion detection method is optical flow. Still the method produces partial detection for low textured images and also computationally expensive due to gradient calculation for each pixel location. The synergistic approach of conventional background subtraction, fast independent component analysis and optical flow methods at different resolutions provide promising detection of targets with reduced time complexity. The dynamic background noise is compensated by the background update. The methodology is validated with benchmark infrared image datasets as well as experimentally generated infrared image sequences of moving targets in the field under various conditions of varying illumination, ambience temperature and the distance of the target from the sensor location. The significant value of F-measure validates the efficiency of the proposed methodology with high confidence of detection and low false alarms.

Item Type: Article
Uncontrolled Keywords: Moving target detection; Thermal infrared imagery; Background subtraction; FastICA; Optical flow
Subjects: CSIO > Computational Instrumentation
Divisions: Computational Instrumentation
Depositing User: Ms. Jyotsana
Date Deposited: 09 Aug 2018 12:15
Last Modified: 09 Aug 2018 12:15
URI: http://csioir.csio.res.in/id/eprint/510

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