Radiometric features for vehicle classification with infrared images

Seçkin Özsaraç; Gözde Bozdağı Akar

doi:10.1117/12.2261718

1 May 2017 Radiometric features for vehicle classification with infrared images

Seçkin Özsaraç, Gözde Bozdağı Akar

Proceedings Volume 10202, Automatic Target Recognition XXVII; 1020204 (2017) https://doi.org/10.1117/12.2261718
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

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.

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Seçkin Özsaraç and Gözde Bozdağı Akar "Radiometric features for vehicle classification with infrared images", Proc. SPIE 10202, Automatic Target Recognition XXVII, 1020204 (1 May 2017); https://doi.org/10.1117/12.2261718

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