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Authors: Sergio Lafuente-Arroyo ; Saturnino Maldonado-Bascón ; Hilario Gómez-Moreno and Pedro Gil-Jiménez

Affiliation: University of Alcalá, Spain

Keyword(s): Intelligent transportation system (ITS), Traffic sign detection and recognition system (TSDRS), AdaBoost, Support vector machines (SVMs), Pattern recognition.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Evolutionary Computing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing ; Symbolic Systems

Abstract: The high variability of road sign appearance and the variety of different classes have made the recognition of pictograms a high computational load problem in traffic sign detection based on computer vision. In this paper false alarms are reduced significantly by designing a cascade filter based on boosting detectors and a generative classifier based on heterogeneity of texture. The false alarm filter allows us to discard many false positives using a reduced selection of features, which are chosen from a wide set of features. Filtering is defined as a binary problem, where all speed limit signs are grouped together against noisy examples and it is the previous stage to the input of a recognition module based on Support Vector Machines (SVMs). In a traffic sign recognition system, the number of candidate blobs detected is, in general, much higher than the number of traffic signs. As asymmetry is an inherent problem, we apply a different treatment for false negatives (FN) and false pos itives (FP). The global filter offers high accuracy. It achieves very low false alarm ratio with low computational complexity. (More)

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Paper citation in several formats:
Lafuente-Arroyo, S.; Maldonado-Bascón, S.; Gómez-Moreno, H. and Gil-Jiménez, P. (2011). FALSE ALARM FILTERING IN A VISION TRAFFIC SIGN RECOGNITION SYSTEM - An Approach based on AdaBoost and Heterogeneity of Texture. In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-8425-40-9; ISSN 2184-433X, SciTePress, pages 269-276. DOI: 10.5220/0003156402690276

@conference{icaart11,
author={Sergio Lafuente{-}Arroyo. and Saturnino Maldonado{-}Bascón. and Hilario Gómez{-}Moreno. and Pedro Gil{-}Jiménez.},
title={FALSE ALARM FILTERING IN A VISION TRAFFIC SIGN RECOGNITION SYSTEM - An Approach based on AdaBoost and Heterogeneity of Texture},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2011},
pages={269-276},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003156402690276},
isbn={978-989-8425-40-9},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - FALSE ALARM FILTERING IN A VISION TRAFFIC SIGN RECOGNITION SYSTEM - An Approach based on AdaBoost and Heterogeneity of Texture
SN - 978-989-8425-40-9
IS - 2184-433X
AU - Lafuente-Arroyo, S.
AU - Maldonado-Bascón, S.
AU - Gómez-Moreno, H.
AU - Gil-Jiménez, P.
PY - 2011
SP - 269
EP - 276
DO - 10.5220/0003156402690276
PB - SciTePress