Automatic number plate recognition system on an ARM-DSP and FPGA heterogeneous SoC platforms

Jeffrey, Zoe; Zhai, Xiaojun; Bensaali, Fayçal; Sotudeh, R.; Ariyaeeinia, Aladdin M.

doi:10.1109/hotchips.2013.7478331

Cited by 5 publications

(1 citation statement)

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“…Nevertheless, using HD images requires more time to process one image since HD images have more pixels than SD images. In fact, this introduces a challenge for designers and engineers to achieve real-time processing [8]. However, researchers were able to overcome this impediment through implementing their systems using field programmable gate array (FPGA), digital signal processor (DSP), or heterogeneous system on chip (SoC).…”

Section: Introductionmentioning

confidence: 99%

Optical character recognition on heterogeneous SoC for HD automatic number plate recognition system

Farhat

Hommos

Al-Zawqari

et al. 2018

J Image Video Proc.

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Automatic number plate recognition (ANPR) systems are becoming vital for safety and security purposes. Typical ANPR systems are based on three stages: number plate localization (NPL), character segmentation (CS), and optical character recognition (OCR). Recently, high definition (HD) cameras have been used to improve their recognition rates. In this paper, four algorithms are proposed for the OCR stage of a real-time HD ANPR system. The proposed algorithms are based on feature extraction (vector crossing, zoning, combined zoning, and vector crossing) and template matching techniques. All proposed algorithms have been implemented using MATLAB as a proof of concept and the best one has been selected for hardware implementation using a heterogeneous system on chip (SoC) platform. The selected platform is the Xilinx Zynq-7000 All Programmable SoC, which consists of an ARM processor and programmable logic. Obtained hardware implementation results have shown that the proposed system can recognize one character in 0.63 ms, with an accuracy of 99.5% while utilizing around 6% of the programmable logic resources. In addition, the use of the heterogenous SoC consumes 36 W which is equivalent to saving around 80% of the energy consumed by the PC used in this work, whereas it is smaller in size by 95%.

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Section: Introductionmentioning

confidence: 99%