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Image analysis and rule-based reasoning for a traffic monitoring system

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3 Author(s)
R. Cucchiara ; Dipt. di Sci. dell'Ingegneria, Modena Univ., Italy ; M. Piccardi ; P. Mello

The paper presents an approach for detecting vehicles in urban traffic scenes by means of rule-based reasoning on visual data. The strength of the approach is its formal separation between the low-level image processing modules and the high-level module, which provides a general-purpose knowledge-based framework for tracking vehicles in the scene. The image-processing modules extract visual data from the scene by spatio-temporal analysis during daytime, and by morphological analysis of headlights at night. The high-level module is designed as a forward chaining production rule system, working on symbolic data, i.e., vehicles and their attributes (area, pattern, direction, and others) and exploiting a set of heuristic rules tuned to urban traffic conditions. The synergy between the artificial intelligence techniques of the high-level and the low-level image analysis techniques provides the system with flexibility and robustness

Published in:

IEEE Transactions on Intelligent Transportation Systems  (Volume:1 ,  Issue: 2 )