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Improved number plate localisation algorithm and its efficient field programmable gate arrays implementation

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3 Author(s)
Xiaojun Zhai ; School of Engineering & Technology, University of Hertfordshire, Hatfield, UK ; Faycal Bensaali ; Soodamani Ramalingam

Number plate localisation is a very important stage in an automatic number plate recognition (ANPR) system and is computationally intensive. This study presents a low complexity with high-detection rate number plate localisation algorithm based on morphological operations together with an efficient multiplier-less architecture based on that algorithm. The proposed architecture has been successfully implemented and tested using a Mentor Graphics RC240 FPGA (field programmable gate arrays) development board equipped with a 4M-gate Xilinx Virtex-4 LX40. Two database sets sourced from the UK and Greece and including 1000 and 307 images, respectively, both with a resolution of 640 × 480, have been used for testing. Results achieved have shown that the proposed system can process an image in 4.7 ms, while achieving a 97.8% detection rate and consuming only 33% of the available area of the FPGA.

Published in:

IET Circuits, Devices & Systems  (Volume:7 ,  Issue: 2 )