Automatic Number Plate Recognition using Random Forest Classifier
- URL: http://arxiv.org/abs/2303.14856v1
- Date: Sun, 26 Mar 2023 23:49:43 GMT
- Title: Automatic Number Plate Recognition using Random Forest Classifier
- Authors: Zuhaib Akhtar and Rashid Ali
- Abstract summary: This paper proposes a number plate recognition method by processing vehicle's rear or front image.
Experimental results reveal that the accuracy of this method is 90.9%.
- Score: 1.0626637240844587
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Automatic Number Plate Recognition System (ANPRS) is a mass surveillance
embedded system that recognizes the number plate of the vehicle. This system is
generally used for traffic management applications. It should be very efficient
in detecting the number plate in noisy as well as in low illumination and also
within required time frame. This paper proposes a number plate recognition
method by processing vehicle's rear or front image. After image is captured,
processing is divided into four steps which are Pre-Processing, Number plate
localization, Character segmentation and Character recognition. Pre-Processing
enhances the image for further processing, number plate localization extracts
the number plate region from the image, character segmentation separates the
individual characters from the extracted number plate and character recognition
identifies the optical characters by using random forest classification
algorithm. Experimental results reveal that the accuracy of this method is
90.9%.
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