Improved number plate character segmentation algorithm and its efficient FPGA implementation

Abstract

Character segmentation is an important stage in Automatic Number Plate Recognition systems as good character separation leads to a high recognition rate. This paper presents an improved character segmentation algorithm based on pixel projection and morphological operations. An efficient architecture based on the proposed algorithm is also presented. The architecture has been successfully implemented and verified using the Mentor Graphics RC240 FPGA (Field Programmable Gate Arrays) development board equipped with a 4M-Gate Xilinx Virtex-4 LX40. A database of 1,000 UK binary NPs with varying resolution has been used for testing the performance of the proposed architecture. Results achieved have shown that the proposed architecture can process a number plate image in 0.2–1.4 ms with 97.7 % successful segmentation rate and consumes only 11 % of the available area in the used FPGA.