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In-vehicle illumination-invariant change detection based on intrinsic images and differences of Gaussians
Author(s): Marco Tektonidis; David Monnin
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Paper Abstract

Image change detection methods allow to automatically detect changes on outdoor routes with respect to a previous time point and to improve the identification of potential threats for vehicles (e.g., improvised explosive devices - IEDs). The change detection task is challenging, mainly due to the arbitrary type of changes and due to the global and local illumination differences. We have developed an illumination-invariant change detection approach based on intrinsic images and differences of Gaussians. The intrinsic images are obtained by the logchromaticity space of color images and in conjunction with reflectance images obtained by homomorphic filtering, illumination-invariant differences images are determined. We employ differences of Gaussians to detect blobs of multiple sizes in the differences images, which describe detected changes. To reduce false positives we propose to weight the scores of the detected blobs based on normalized cross-correlation, and to enforce temporally consistent changes we employ a temporal filtering scheme. The approach has been successfully applied to image sequences acquired on outdoor routes at different time points, demonstrating the consistent detection of changes over time, and the invariance to illumination differences, including shadows.

Paper Details

Date Published: 10 May 2019
PDF: 10 pages
Proc. SPIE 11012, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV, 1101213 (10 May 2019); doi: 10.1117/12.2521446
Show Author Affiliations
Marco Tektonidis, French-German Research Institute of Saint-Louis (France)
David Monnin, French-German Research Institute of Saint-Louis (France)


Published in SPIE Proceedings Vol. 11012:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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