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. 2016 Apr 5;4:13. doi: 10.1186/s40349-016-0058-7

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© Sellani et al. 2016

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 3 — Image processing algorithm. a The original image is obtained as a matrix with 140 × 140 pixels, and each pixel is represented by a temperature value, as captured by the infrared camera. b A contrast enhancement of the normalized gray-scale image using histogram equalization is performed, and the user is able to correctly select the ROI. c Zoom of the selected ROI. d After the determination of an intensity threshold, the algorithm separates and binarizes (turns image pixels in black and white) the heating area from the background. e Once the heating area is isolated, the histogram with the temperatures inside the ROI is depicted, and X _T and SD_T can be estimated (using the temperature data from the original image)