Title :
License plate recognition system using hybrid neural networks
Author :
Seetharaman, Vivek ; Sathyakhala, A. ; Vidhya, N.L.S. ; Sunder, P.
Author_Institution :
Dept. of Comput. Sci., Sri Ramakrishna Eng. Coll., Coimbatore, India
Abstract :
License plate recognition is one of the machine vision problem which has a wide range of practical applications. Various methodologies have been suggested with varying efficiencies. In this paper we propose an ASIC implementation of a new methodology which uses a hybrid neural network in conjunction with the weight based density map technique for the license plate localization. The combination of the two techniques, that have already been used individually, has produced higher recognition rates. Further the ASIC implementation means that the time complexity of the methodology can be completely ignored. The system design and the experimental results of the system have been discussed briefly.
Keywords :
application specific integrated circuits; character recognition; computational complexity; computer vision; image segmentation; neural nets; ASIC; hybrid neural networks; license plate recognition system; machine vision; time complexity; weight based density map technique; Application software; Application specific integrated circuits; Computer science; Educational institutions; Histograms; Image recognition; Licenses; Machine vision; Neural networks; Vehicles;
Conference_Titel :
Fuzzy Information, 2004. Processing NAFIPS '04. IEEE Annual Meeting of the
Print_ISBN :
0-7803-8376-1
DOI :
10.1109/NAFIPS.2004.1336309