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Proceedings Paper

Infrared image segmentation based on region of interest extraction with Gaussian mixture modeling
Author(s): Seokwon Yeom
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Paper Abstract

Infrared (IR) imaging has the capability to detect thermal characteristics of objects under low-light conditions. This paper addresses IR image segmentation with Gaussian mixture modeling. An IR image is segmented with Expectation Maximization (EM) method assuming the image histogram follows the Gaussian mixture distribution. Multi-level segmentation is applied to extract the region of interest (ROI). Each level of the multi-level segmentation is composed of the k-means clustering, the EM algorithm, and a decision process. The foreground objects are individually segmented from the ROI windows. In the experiments, various methods are applied to the IR image capturing several humans at night.

Paper Details

Date Published: 1 May 2017
PDF: 6 pages
Proc. SPIE 10202, Automatic Target Recognition XXVII, 102020C (1 May 2017); doi: 10.1117/12.2263673
Show Author Affiliations
Seokwon Yeom, Daegu Univ. (Korea, Republic of)

Published in SPIE Proceedings Vol. 10202:
Automatic Target Recognition XXVII
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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