Next Article in Journal
A Numerical Simulation of Melting of Ice Heated from above
Previous Article in Journal
Fragmentation of a Non-Rotating Ni19 Cluster: A Molecular Dynamics Study
Article Menu

Article Versions

Export Article

Open AccessArticle
Math. Comput. Appl. 1996, 1(2), 1-6; doi:10.3390/mca1020001

A New Technique to Process and Recognize Barcodes Using Induction

Sakarya Univ. Engineering Faculty, Industrial Eng Dept., Escntepe, Adapazaı, Turkey
TÜVASAŞ, Adapazaı, Turkey
Author to whom correspondence should be addressed.
Published: 1 December 1996
Download PDF [2643 KB, uploaded 21 April 2016]


In this paper, a new technique to recognize and process Barcodes is introduced. The technique employs Inductive Learning. It is suitable to use, for example, in a factory to control the workers, staff, stock etc. In this technique only vertical lines are considered while the spaces in between are ignored. This results faster processing. Each Barcode is considered to represent an item. For each Barcode a rule is extracted from the necessary information using Inductive Learning. So the unnecessary information is eliminated. This causes faster processing time and less amount of memory. In order to use this technique no special hardware is required. Only a PC and a Barcode reader is enough.
Keywords: Artificial Intelligence; Inductive Learning; Barcode; Expert Systems Artificial Intelligence; Inductive Learning; Barcode; Expert Systems
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Aksoy, M.S.; Bayram, M. A New Technique to Process and Recognize Barcodes Using Induction. Math. Comput. Appl. 1996, 1, 1-6.

Show more citation formats Show less citations formats

Article Metrics

Article Access Statistics



[Return to top]
Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top