Authors: K. Hanton, J. Sunde, M. Butavicius, V. Gluscevic
Addresses: School of Electrical and Information Engineering, Division of Information Technology, Engineering and the Evironment, University of South Australia, Mawson Lakes campus, Mawson Lakes Boulevard, SA 5095, Australia. ' Weapons System Division, Defence Science and Technology Organisation, PO Box 1500, Edinburgh SA 5111, Australia. ' School of Psychology, University of Adelaide, Adelaide SA 5005, Australia. ' RAAF, JEWOSU, West Ave, Edinburgh, SA 5111, Australia
Abstract: The ability to detect and recognise dangerous objects at a safe distance is a very important task in a number of defence, police and security applications. In this paper, we look at ways of increasing the effectiveness of infrared imagery for object recognition through processes such as super-resolution image reconstruction and deconvolution methods. In this paper, we propose two techniques for assessing image quality improvement: operator assessment and edge detection; and report on some initial work recently undertaken.
Keywords: infrared imaging; human detection; performance measures; image enhancement; super-resolution images; image quality; object recognition; image reconstruction; image deconvolution; operator assessment; edge detection; dangerous objects.
International Journal of Intelligent Defence Support Systems, 2010 Vol.3 No.1/2, pp.5 - 21
Published online: 15 Jun 2010 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article