RECOGNITION DESIGN OF LICENSE PLATE AND CAR TYPE USING TESSERACT OCR AND EmguCV
Abstract: The goal of the
research is to design and implement software that can recognize license plates
and car types from images. The method used for the research is soft computing
using library of EmguCV. There are four phases in creating the software, i.e.,
input image process, pre-processing, training processing and recognition.
Firstly, user enters the car image. Then, the program reads and does
pre-processing the image from bitmap form into vector. The next process is
training process, which is learning phase in order the system to be able
recognize an object (in this case license plate and car type), and in the end
is the recognition process itself. The result is data about the car types and
the license plates that have been entered. Using simulation, this software
successfully recognized license plate by 80.223% accurate and car type 75%
accurate.
Author: Antonius Herusutopo,
Rizky Zuhrudin, Willy Wijaya, Yuka Musiko
Journal Code: jptinformatikagg120017
