In this paper we describe a plate-recognition system for access control to restricted areas. The system we propose is based on vision, neural networks and a neuro-fuzzy system. Vision is used to detect the license-plate and to single out the characters it contains, while a neural network-based classifier is used to "read" the plate. The resulting string is then matched to a "white list" of allowed plates, to check the transit authorization. In case matching fails, a neuro-fuzzy agent analyses the features of the mismatch, to filter out possible false alarms and to optimize the workload for the human supervisor that has to validate the alarm.
Access control system with neuro-fuzzy supervision
2001-01-01
689677 byte
Conference paper
Electronic Resource
English
Access Control System with Neuro-Fuzzy Supervision
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