Overview / Usage

License plate recognition is an important component of modern intelligent transportation systems (ITS). Generally vehicle license plate recognition is divided into several steps including license plate extraction, image region which contains a license plate, character segmentation, and character recognition. In License plate recognition the image is processed to extract the license number. The extracted information can be used with or without a database in many applications, such as electronic payment systems toll payment, parking fee payment, and freeway and arterial monitoring systems for traffic surveillance. If a vehicle tries to cross traffic rules, its license number is extracted and information regarding the offense along with the license plate no is sent to the Traffic Control Section for further legal actions to be taken. An alarm is raised to inform the on field policeman about the offense. It should also be generalized to process license plates from different nations, provinces, or states.

Methodology / Approach

LPR sometimes called ALPR (Automatic License Plate Recognition) has 3 major stages.

1. License Plate Detection: This is the first and probably the most important stage of the system. It is at this stage that the position of the license plate is determined. The input at this stage is an image of the vehicle and the output is the license plate.
2. Character Segmentation: It’s at this stage the characters on the license plate are mapped out and segmented into individual images.
3. Character Recognition: This is where we wrap things up. The characters earlier segmented are identified here. We’ll be using machine learning for this.

Technologies Used

Language used: Python 3.5
Major Libraries/packages: Numpy(library for Scientific computing), Open CV 3(Computer vision library) etc
Algorithm used : K nearest neighbour
Environment: Anaconda
IDE: Spyder

Repository

https://github.com/mrkazmi333/License_Plate_Recognition_Open_CV_3_Python

Other links

• https://facebook.com/hackachu