TELKOMNIKA Telecommunication Computing Electronics and Control
Digital transformation for shipping container terminals using automated container code recognition

TELKOMNIKA Telecommunication Computing Electronics and Control
Digital transformation for shipping container terminals using automated container code recognition

Character isolation
Character recognition
Container codes recognition
Histogram of oriented gradients
Support vector machine

Due to the sweeping waves of global industry development, the number of
containers passing through terminal ports increases every day. Therefore, it
is essential to automate the identification process for the container codes to
replace the manual identification for more efficient logistics and safer
workplace. This paper aims to design and evaluate the performance of such a
system. Specifically, automated container codes recognition (ACCR) has
been implemented. This is a novel container tracking model based on image
processing algorithms and machine learning (ML) algorithms to be applied
in ports. There are three steps in this system: character detection, character
isolation, and character recognition. The first step is to identify an area with
10 digits and 26 capitals. After detecting the text area, the second step is to
separate the characters. Each character is recognized in the last step by the
classification method. In particular, features are extracted with the histogram
of oriented gradients (HOG) algorithm and support vector machines (SVMs)
for training and prediction. The trained ML model is then used to classify
characters and digits according to what it has learned. In general, the digital
technologies in logistics and container management in ports will benefit
from the proposed algorithms.

Hoang-Sy Nguyen, Cong-Danh Huynh, Nhat-Quan Bui

http://telkomnika.uad.ac.id

Dec 28, 2022

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