PROBABILISTIC MODELING AND FUSION FOR IMAGE FEATURE EXTRACTION WITH APPLICATIONS TO LICENSE PLATE DETECTION

Rami Al-Hmouz, Subhash Challa, Duc Vo

2007

Abstract

The paper proposes a novel feature fusion concept for object extraction. The image feature extraction process is modeled as a feature detection problem in noise. The geometric features are probabilistically modeled and detected under various detection thresholds. These detection results are then fused within the Bayesian framework to obtain the final features for further processing. Along with a probabilistic model, pixels voting algorithm is also tested through binary threshold variation. The performance of these approaches is compared with the traditional approaches of image feature extraction in the context of automatic license plate detection problem.

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Paper Citation


in Harvard Style

Al-Hmouz R., Challa S. and Vo D. (2007). PROBABILISTIC MODELING AND FUSION FOR IMAGE FEATURE EXTRACTION WITH APPLICATIONS TO LICENSE PLATE DETECTION . In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 978-972-8865-73-3, pages 398-403. DOI: 10.5220/0002054003980403


in Bibtex Style

@conference{visapp07,
author={Rami Al-Hmouz and Subhash Challa and Duc Vo},
title={PROBABILISTIC MODELING AND FUSION FOR IMAGE FEATURE EXTRACTION WITH APPLICATIONS TO LICENSE PLATE DETECTION},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2007},
pages={398-403},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002054003980403},
isbn={978-972-8865-73-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - PROBABILISTIC MODELING AND FUSION FOR IMAGE FEATURE EXTRACTION WITH APPLICATIONS TO LICENSE PLATE DETECTION
SN - 978-972-8865-73-3
AU - Al-Hmouz R.
AU - Challa S.
AU - Vo D.
PY - 2007
SP - 398
EP - 403
DO - 10.5220/0002054003980403