Hardware architecture for real-time license plate character recognition based on EWM2DPCA

Boyu Gu, Qiang Zhang, Zhenhuan

Abstract

An embedded hardware architecture for license plate character recognition is designed and implemented on an FPGA (field programmable gate array). The architecture is based on EWM2DPCA (eigen weighted modular two-dimensional principal component analysis) which is presented in this paper. Three kinds of processing elements are included in the hardware architecture, projection element is designed for matrix multiplication operations of feature extraction, weighted distances between input character and each class in training database are computed in distance element, and the nearest neighbor classification is carried out in classification element. Parallel and pipeline acceleration technique are combined in the hardware architecture. Experimental results show that the recognition rate of the proposed algorithm is improved, and the hardware architecture achieves high performance, which is practical and reasonable.

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