ASELEBE MICHAEL OLUWASEGUN
ARTMENT OF COMPUTER SCIENCE,
INSTITUTE OF BASIC AND APPLIED SCIENCE
KWARA STATE POLYTECNIC, ILORIN.
IN PARTIAL FULFILMENT OF THE REQUIREMENT
FOR THE AWARD OF HIGHER NATIONAL DIPLOMA
IN COMPUTER SICENCE
This study focuses on barcode recognition from images of barcode stamped products, acquired by different cameras. First step in recognition of barcode data is achieving barcode localization. For this purpose, a Fast Hough Transform Approximation has been developed. With this method, barcode localization and the angular orientation of the barcode is obtained. In order to decipher barcode data, the scan line obtained by barcode localization and angular orientation information are used. However, the image resolution has to be good enough so that the bar code data could be read properly. In this work, image quality is improved with methods of B-Spline Smoothing and super-resolution techniques. Later, barcode data is deciphered via match filtering. The proposed barcode reading system is tested and results are discussed.
BARCODE is a method of automatic identification & data collection, also known as the “Universal Product Code” (UPC). BARCODE is use the Binary System for coding & decoding. It has the series of bars & space representing alpha numeric information. Each bar represent “1” & space represent “0”. Barcodes are very popular and are seen on almost every consumer products. Barcodes provide reliable data string and quick input into a computer system. In this manner, price and product description can be obtained very fast.
Example of the bar code from a 1.5-liter bottle of Diet Coke
AIM AND OBJECTIVES OF BARCODE
The Aim is to acquire a barcode scanner system to streamline and improve an outdated seized asset/evidence and property tracking system, utilizing a barcode technology to facilitate the collection, management, transfer/movement, storage, and disposition of property. The specific objectives of the seminar are to:
• Identify a barcode system that will provide a means to electronically track seized assets to replace the OCI3400, Certified Inventory of Evidence (CIE) and to replace form HHS-22 for tracking property
• Integrate the barcode technology into the OCI Automated Investigative Management System (AIMS) Oracle 10g database system. (I.e. currently, all evidence related data is manually entered into our AIMS system. OCI needs to be able to import data (including images) into our AIMS system from the barcoding system. Therefore, the barcoding system must be able to export data into CSV (comma separated values) format so that an AIMS import process (to be developed by OCI personnel) can import data periodically. Exact specifications of the exported CSV data will be defined by OCI and vendor.
• Design a system that will be utilized nationwide in remote locations on search warrant sites to log seized assets/evidence, barcode, and generate forms/reports remotely. • Customize a solution allowing OCI the capabilities to enhance or expand the barcoding software.
PROBLEMS OF BARCODE
• Disorientations, obstruction by dirt, mist, protrusions and damage all because failed reads or misreads.
• They have to be read at line of sight, usually at distances below one meter.
• Scanners are delicate and expensive, causing problems for e.g., New Zealand sheep farmers.
• Very little data is stored and it is read-only and not secure or even covert.
• The image is relatively large and ugly. It is impossible to put a practicable barcode on, say an earring or a single wrap of candy because of appearance and the need for high accuracy printing, substrate stability, etc.,.
• Simultaneous non-collision scanning of multiple images/products is near impossible. ...
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