Performance Measure of Car Parking By Using RFID and OCR

Abstract

Automatic number plate recognition plays a significant role in
several applications and a number of techniques have been
proposed. The proposed system consists of two modules: a
number plate locating module and a number plate
identification module. The previous characterized by fuzzy
orders attempts to extract number plates from an input image,
while the final conceptualized in terms of neural themes wants
to identify the number present in a plate. These applications
vary from complex security systems to commons areas and
from parking entrance to city traffic control. The core idea of
this work is to solve the realistic problem of car identification
for real scenes. All steps of the process, from image
acquisition to optical character recognition are considered to
accomplish an automatic identification of number plates. OCR
used to identify an optical refined written characters vehicle
number plate is based on template matching. In last phase the
letters on the number plate are converted into string or texts
format. It can be used with all type of country rules or plates
design. The algorithm is tested over different images with
different size of vehicle images. In proposed system, number
plates are recognizing, with the success rate of 92% and 95%
respectively.