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Proceedings Paper

Radiometric features for vehicle classification with infrared images
Author(s): Seçkin Özsaraç; Gözde Bozdağı Akar
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Paper Abstract

A vehicle classification system, which uses features based on radiometry, is developed for single band infrared (IR) image sequences. In this context, the process is divided into three components. These are moving vehicle detection, radiance estimation, and classification. The major contribution of this paper lies in the usage of the radiance values as features, other than the raw output of IR camera output, to improve the classification performance of the detected objects. The motivation behind this is that each vehicle class has a discriminating radiance value that originates from the source temperature of the object modified by the intrinsic characteristics of the radiating surface and the environment. As a consequence, significant performance gains are achieved due to the use of radiance values in classification for the utilized measurement system.

Paper Details

Date Published: 1 May 2017
PDF: 14 pages
Proc. SPIE 10202, Automatic Target Recognition XXVII, 1020204 (1 May 2017); doi: 10.1117/12.2261718
Show Author Affiliations
Seçkin Özsaraç, ASELSAN A.S. (Turkey)
Gözde Bozdağı Akar, Middle East Technical Univ. (Turkey)

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

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