Automatic arabic number plate recognition

The proposed license plate recognition system is tested against a real video of two hours and the accuracy was 81% and average time per frame was 24 msec/frame. This paper presents a license plate recognition system for the Egyptian plates introduced in 2008. The proposed system is composed of three main stages; localization & skew correction stage, segmentation stage, and recognition stage. The localization stage uses the main feature of the plate where high contrast text-background is tagged with colored or gray area, to find the plate candidates in the image and to measure the skew angle. In segmentation stage, connected component analysis is applied to find objects belong to license number. The objects will be analyzed to attach diacritic and over segmented objects to each other to form a group of recognizable objects. The final objects will be split to digits and letter groups. In recognition stage, an adapted template match technique is introduced to recognize the digits and letter groups separately after normalizing them. The system is tested against a real video of two hours and the accuracy was 81% and average time per frame was 24 msec/frame.

Automatic Iraqi license plate recognition system using back propagation neural network (BPNN)

ANPR - Dahua CEE Region

Ahmed Abd El-Rahman - GBM

Hands-free access with license plate recognition

An automated license plate detection and recognition system based on wavelet decomposition and CNN - ScienceDirect

Automatic arabic number plate recognition (ANPR) for Egyptian cars licence plates.

PDF) Automatic Arabic Number Plate Recognition

PDF) Practical Automatic Arabic License Plate Recognition System

Ahmed Abd El-Rahman - GBM

PDF) Libyan Vehicle License Plate Recognition System

Extraction of the data sets from image

Faten ZAKI, Research Director