@Article{, title={Iraqi License Plate Detection and Segmentation based on Deep Learning}, author={Ghida Yousif Abbass and Ali Fadhil Marhoon}, journal={Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية}, volume={17}, number={2}, pages={102-107}, year={2021}, abstract={Nowadays, the trend has become to utilize Artificial Intelligence techniques to replace the human’s mind in problem solving. Vehicle License Plate Recognition (VLPR) is one of these problems in which the computer outperforms the human being in terms of processing speed and accuracy of results. The emergence of deep learning techniques enhances and simplifies this task. This work emphasis on detecting the Iraqi License Plates based on SSD Deep Learning Algorithm. Then Segmenting the plate using horizontal and vertical shredding. Finally, the K-Nearest Neighbors (KNN) algorithm utilized to specify the type of car. The proposed system evaluated by using a group of 500 different Iraqi Vehicles. The successful results show that 98% regarding the plate detection, and 96% for segmenting operation.

} }