Infrared image segmentation through iterative thresholding

Fabio Lavagetto

doi:10.1117/12.21219

1 September 1990 Infrared image segmentation through iterative thresholding

Fabio Lavagetto

Proceedings Volume 1295, Real-Time Image Processing II; (1990) https://doi.org/10.1117/12.21219
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

A real time segmentation algorithm for infrared sequences is presented, based on the iterative application of thermal histogram processing and thresholding. The segmentation algorithm is intrinsically not sequential and may therefore be decomposed into a graph of concurrent processing tasks well suited to a parallel implementation. The algorithm is based on the assumption that two pixel populations are present, namely object and background. Since in this hypothesis the separation goodness function should have one single maximum, the algorithm forces this behaviour by redistributing the area of the histogram, i.e. by progressively brightening the target population. An initialization phase finds out potential target areas throughout the current frame in cooperation with a temporal tracking and labeling task, and compiles the search windows set. For each search window the thermal histogram is computed. Then a family of modified histograms is obtained by removing greater and greater areas from the hot tail of the original histogram and by replacing it with an impulse of the same area at the highest extreme of the thermal range. Each of these histograms enters a module which computes a separation goodness function. The separation function presents two adjacent segments: the high thermal segment and the low thermal segment. The former is a constant segment which lasts from the high extreme of the thermal range down to the lowest thermal value of the removed area, the latter has a variable shape and lasts as far as the lowest extreme of the thermal range. The iteration is stopped as soon as the variable segment reaches a monotonically decreasing behaviour. The boundary value between the two segments is chosen as threshold within that window. Experimental results are presented.

Citation Download Citation

Fabio Lavagetto "Infrared image segmentation through iterative thresholding", Proc. SPIE 1295, Real-Time Image Processing II, (1 September 1990); https://doi.org/10.1117/12.21219

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KEYWORDS

Image segmentation

Image processing

Infrared radiation

Thermography

Infrared imaging

Thermal modeling

Algorithm development

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