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Proceedings Paper

Real-time algorithms for human versus animal classification using a pyroelectric sensor
Author(s): Jakir Hossen; Eddie Jacobs; Srikant Chari
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Paper Abstract

Classification of human and animal targets imaged by a linear pyroelectic array senor presents some unique challenges especially in target segmentation and feature extraction. In this paper, we apply two approaches to address this problem. Both techniques start with the variational energy functional level set segmentation technique to separate the object from background. After segmentation, in the first technique, we extract features such as texture, invariant moments, edge, shape information, and spectral contents of the segmented object. These features are fed to classifiers including Naïve Bayesian (NB), and Support Vector Machine (SVM) for human against animal classification. In the second technique, the speeded up robust feature (SURF) extraction algorithm is applied to the segmented objects. A code book technique is used to classify objects based on SURF features. Human and animal data acquired-using the pyroelectric sensor in different terrains, are used for performance evaluation of the algorithms. The evaluation indicates that the features extracted in the first technique in conjunction with the NB classifier provide the highest classification rates. While the SURF feature plus code book approach provides a slightly lower classification rate, it provides better computational efficiency lending itself to real time implementation.

Paper Details

Date Published: 6 June 2013
PDF: 12 pages
Proc. SPIE 8711, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII, 871103 (6 June 2013); doi: 10.1117/12.2015458
Show Author Affiliations
Jakir Hossen, The Univ. of Memphis (United States)
Eddie Jacobs, The Univ. of Memphis (United States)
Srikant Chari, The Univ. of Memphis (United States)


Published in SPIE Proceedings Vol. 8711:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII
Edward M. Carapezza, Editor(s)

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