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Feature evaluation for target/background discrimination in image sequences taken by approaching sensors

: Schoene, R.; Meidow, J.; Mauer, E.

Preprint urn:nbn:de:0011-n-1887881 (870 KByte PDF)
MD5 Fingerprint: b24748978a02e195a94934373b1a3724
Copyright 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Erstellt am: 17.4.2012

Kadar, I. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Signal processing, sensor fusion, and target recognition XIX : 5 - 7 April 2010, Orlando, Florida, United States
Bellingham, WA: SPIE, 2010 (Proceedings of SPIE 7697)
ISBN: 978-0-8194-8161-0
Paper 769718
Conference "Signal Processing, Sensor Fusion, and Target Recognition" <19, 2010, Orlando/Fla.>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()
automatic registration; feature extraction; ROC curves analysis; Mann Whitney U-Test

The conspicuity of different targets in image sequences taken by approaching sensors is addressed in applications such as the assessment of camouflage effectiveness or the performance evaluation of autonomous systems. In such evaluation processes the consideration of background characteristics is essential due to the propensity to confuse target and background signatures. Several discriminating features of target and background signature can be derived. Furthermore, the changing aspect and spatial resolution during an approach on a target have to be taken into account. Considering salient points in image sequences, we perform a nominal/actual value comparison by evaluating the receiver operating characteristic (ROC) curve for the detections in each image. Hence, reference regions for targets and backgrounds are provided for the entire image sequence by means of robust image registration. The consideration of the uncertainty for the temporal progression of the ROC curve enables hypothesis testing for well-founded statements about the significance of the determined distinctiveness of targets with respect to their background. The approach is neither restricted to images taken by IR sensors nor applicable to low level image analysis steps only, but can be considered as a general method for the assessment of feature evaluation and target distinctiveness. The analysis method proposed facilitates an objective comparison of object appearance with both, its relevant background and other targets, using different image analysis features. The feasibility and the usefulness of the approach are demonstrated with real data recorded with a FLIR sensor during a field trial on a bare and mock-up target.