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Proceedings Paper

Model to predict the probability of recognition of shapes viewed through a thermal imager
Author(s): Alison M. Fairhurst; Alan H. Lettington; Kevin St. John Murphy
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Paper Abstract

A computer model has been developed to predict the probability of recognition of particular shapes when viewed through a thermal imager employing either scanned or focal plane array detectors. This model is based on the results of a series of psychophysical trials during which human observers have considered over 120,000 images of shapes having a range of initial contrasts, and which have been degraded by various combinations of blurring and sampling. These computer generated images were presented to the observers in a random order and with a random degradation, using programs to select images and display them on a computer monitor. After each presentation the observer decided which was the most likely shape to represent the image displayed on the screen. The responses collected have been used to calculate the human recognition probability of each image. A correlation has been found between the probability of recognition of any specified degraded shape and the relative contrast between the image of that shape, and the image of a similarly degraded circle of the same area. The present work is related to earlier models of human detection and recognition probabilities, and has recently been extended to include the effect of contrast.

Paper Details

Date Published: 27 June 1996
PDF: 7 pages
Proc. SPIE 2744, Infrared Technology and Applications XXII, (27 June 1996); doi: 10.1117/12.243503
Show Author Affiliations
Alison M. Fairhurst, Univ. of Reading (United Kingdom)
Alan H. Lettington, Univ. of Reading (United Kingdom)
Kevin St. John Murphy, Defence Research Agency Malvern (United Kingdom)


Published in SPIE Proceedings Vol. 2744:
Infrared Technology and Applications XXII
Bjorn F. Andresen; Marija S. Scholl, Editor(s)

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