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.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.