Edge Computing for License Plate Recognition

This demo captures license plates using machine learning neural network algorithms to identify. The Arm® Cortex®-M4 core supports the DSP instruction to speed up algorithms. In addition, the information can be transmitted to the cloud through Wi-Fi or NB-IoT to realize the image recognition on an edge device.

Features

Board 1: Edge Computing for License Plate Recognition
-	Supports multiple image pre-processing algorithms
-	Supports convolutional neural network (CNN)
-	Supports 320*240 TFT LCD Panel to show the image of original License Plate
-	Supports Wi-Fi module to transfer the recognition result to the 2nd board
Board 2: TFT LCD Control Board to show the recognition result
-	Uses Wi-Fi module to receive the recognition result and show the result on the 320*240 TFT LCD Panel

Specifications

M480 (32-bit Arm® Cortex®-M4F)
-	CPU frequency up to 192 MHz
-	Built-in up to 512 KB Flash and 160 KB SRAM
-	Built-in DSP Accelerator to finish the image recognition in 0.5 seconds
-	Supports Camera capture interface and hardware binarization

System Block Diagram

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Consumer

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Audio / Video

Edge Computing for License Plate Recognition

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