Paper
2 February 2006 Intelligent MRTD testing for thermal imaging system using ANN
Junyue Sun, Dongmei Ma
Author Affiliations +
Proceedings Volume 6031, ICO20: Remote Sensing and Infrared Devices and Systems; 603111 (2006) https://doi.org/10.1117/12.668040
Event: ICO20:Optical Devices and Instruments, 2005, Changchun, China
Abstract
The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task, for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type, the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP, but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly, we use frame grabber to capture the 4-bar target image data. Then according to image gray scale, we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets, along with known target visibility, are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm, demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Junyue Sun and Dongmei Ma "Intelligent MRTD testing for thermal imaging system using ANN", Proc. SPIE 6031, ICO20: Remote Sensing and Infrared Devices and Systems, 603111 (2 February 2006); https://doi.org/10.1117/12.668040
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KEYWORDS
Minimum resolvable temperature difference

Thermography

Imaging systems

Spatial frequencies

Image segmentation

Neural networks

Visibility

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