Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/6494

Title: Real-time multi barcode reader for industrial applications
Authors: Zafar, Iffat
Zakir, Usman
Edirisinghe, Eran A.
Keywords: Two-dimensional barcodes
Barcode detection/decoding
Datamatrix
Issue Date: 2010
Publisher: © 2010 SPIE
Citation: ZAFAR, I., ZAKIR, U. and EDIRISINGHE, E.A., 2010. IN: Kehtarnavaz, N. (ed.), Real-time multi barcode reader for industrial applications. Real-Time Image and Video Processing 2010, Proc. of SPIE, 7724, 772404, 10pp.
Abstract: The advances in automated production processes have resulted in the need for detecting, reading and decoding 2D datamatrix barcodes at very high speeds. This requires the correct combination of high speed optical devices that are capable of capturing high quality images and computer vision algorithms that can read and decode the barcodes accurately. Such barcode readers should also be capable of resolving fundamental imaging challenges arising from blurred barcode edges, reflections from possible polyethylene wrapping, poor and/or non-uniform illumination, fluctuations of focus, rotation and scale changes. Addressing the above challenges in this paper we propose the design and implementation of a high speed multi-barcode reader and provide test results from an industrial trial. To authors knowledge such a comprehensive system has not been proposed and fully investigated in existing literature. To reduce the reflections on the images caused due to polyethylene wrapping used in typical packaging, polarising filters have been used. The images captured using the optical system above will still include imperfections and variations due to scale, rotation, illumination etc. We use a number of novel image enhancement algorithms optimised for use with 2D datamatrix barcodes for image de-blurring, contrast point and self-shadow removal using an affine transform based approach and non-uniform illumination correction. The enhanced images are subsequently used for barcode detection and recognition. We provide experimental results from a factory trial of using the multi-barcode reader and evaluate the performance of each optical unit and computer vision algorithm used. The results indicate an overall accuracy of 99.6 % in barcode recognition at typical speeds of industrial conveyor systems.
Description: Copyright 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. This paper can also be found at: http://dx.doi.org/10.1117/12.854645
Version: Published
DOI: 10.1117/12.854645
URI: https://dspace.lboro.ac.uk/2134/6494
Appears in Collections:Conference Papers (Computer Science)

Files associated with this item:

File Description SizeFormat
Eran2.pdf11.03 MBAdobe PDFView/Open

 

SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.