Number Plate Recognition (ANR) using Crimmins Complementary Hulling Algorithm

Abstract

The crime of stolen vehicle in the metro city has rise now a days, to track the stolen vehicle the cops required the help of automatic Number Plate recognition (ANR). The use of ANR are not limited to the track stolen car but many more like automatic car parking system, automatic toll collection system etc. but the ANR system has many issues in implementation. Some ANR uses hardware repository to track the number of the vehicle which uses the CCTV camera to capture vehicle image. the extracting the number from the vehicle image. the image has to be noise free. In proposed method I implemented the new approach to remove the noise from vehicle image which is generated by the camera due to low sunlight as a result image will contain salt and paper noise. In proposed method crimmins speckle algorithm is used to remove the salt and paper noise.

ANPR Streamlining for Enhanced Service with CRM

“…Their findings underscored the system's robustness and its potential to contribute to intelligent transportation systems and enhance security in parking areas. Kiran Sonavane's work [4] honed in on the crucial role of ANPR systems in tracking stolen vehicles in urban environments. Their approach tackled issues related to poor illumination and noise in CCTV images through the application of the Crimmins Speckle Algorithm.…”