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Proceedings Paper

Automated recognition and detection of dismounts and vehicles using close-in urban hyperspectral images
Author(s): Shamsaddin Karimkhan; Karmon Vongsy; Arnab K. Shaw; Devert Wicker
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Paper Abstract

Advances in Hyperspectral imaging (HSI) sensor offer new avenues for precise detection, identification and characterization of materials or targets of military interest. HSI technologies are capable of exploiting 10s to 100s of images of a scene collected at contiguous or selective spectral bands to seek out mission-critical objects. In this paper, we develop and analyze several HSI algorithms for detection, recognition and tracking of dismounts, vehicles and other objects. Preliminary work on detection, classification and fingerprinting of dismount, vehicle and UAV has been performed using visible band HSI data. The results indicate improved performance with HSI when compared to traditional EO processing. All the detection and classification results reported in this paper were based on single HSI pixel used for testing. Furthermore, the close-in Hyperspectral data were collected for the experiments at indoor or outdoor by the authors. The collections were taken in different lighting conditions using a visible HSI sensor. The algorithms studied for performance comparison include PCA, Linear Discriminant Analysis method (LDA), Quadratic classifier and Fisher's Linear Discriminant and comprehensive results have been included in terms of confusion matrices and Receiver Operating Characteristic (ROC) curves.

Paper Details

Date Published: 7 May 2007
PDF: 12 pages
Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65650X (7 May 2007); doi: 10.1117/12.723211
Show Author Affiliations
Shamsaddin Karimkhan, Wright State Univ. (United States)
Karmon Vongsy, Wright State Univ. (United States)
Arnab K. Shaw, Wright State Univ. (United States)
Devert Wicker, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 6565:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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