Recovery of the distorted barcodes for mobile applications

Barcodes have been widely used in business for their fast information acquisition capability and large information storage capacity. As technology advances, almost all mobile phones are embedded with camera devices, and these devices can be used for barcode symbol recognition, typical examples of...

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Main Author: Lin, Dongli.
Other Authors: Jiang Xudong
Format: Final Year Project
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/17889
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-178892023-07-07T15:49:11Z Recovery of the distorted barcodes for mobile applications Lin, Dongli. Jiang Xudong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Barcodes have been widely used in business for their fast information acquisition capability and large information storage capacity. As technology advances, almost all mobile phones are embedded with camera devices, and these devices can be used for barcode symbol recognition, typical examples of the barcodes are EAN barcode, PDF417 and QR-code. However, the barcode images produced by the camera phones have undergone serious distortions such that it has created troubles in subsequent barcode decoding process. There are various reasons that can cause the degradation of the barcode images, which include camera noise, motion blur caused by relative motion between camera and object, defocus blur, environmental lightings and many others. In this project, the aim is to investigate the various distortions introduced in the barcode capturing process and propose effective methods to rectify the distortions. We shall focus on a typical barcode symbol, PDF417. Two sequential image blur reduction algorithms for mobile phones will be studied [1]. The first algorithm operates on low-exposure image, which shifts the image’s brightness to the brighter side. The second algorithm enhances the blurred image contrast. Further image processing methodology on how to achieve better image quality and improvements improving in the success rate of decoding will be investigated and discussed in this report. Bachelor of Engineering 2009-06-17T06:16:25Z 2009-06-17T06:16:25Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/17889 en Nanyang Technological University 78 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Lin, Dongli.
Recovery of the distorted barcodes for mobile applications
description Barcodes have been widely used in business for their fast information acquisition capability and large information storage capacity. As technology advances, almost all mobile phones are embedded with camera devices, and these devices can be used for barcode symbol recognition, typical examples of the barcodes are EAN barcode, PDF417 and QR-code. However, the barcode images produced by the camera phones have undergone serious distortions such that it has created troubles in subsequent barcode decoding process. There are various reasons that can cause the degradation of the barcode images, which include camera noise, motion blur caused by relative motion between camera and object, defocus blur, environmental lightings and many others. In this project, the aim is to investigate the various distortions introduced in the barcode capturing process and propose effective methods to rectify the distortions. We shall focus on a typical barcode symbol, PDF417. Two sequential image blur reduction algorithms for mobile phones will be studied [1]. The first algorithm operates on low-exposure image, which shifts the image’s brightness to the brighter side. The second algorithm enhances the blurred image contrast. Further image processing methodology on how to achieve better image quality and improvements improving in the success rate of decoding will be investigated and discussed in this report.
author2 Jiang Xudong
author_facet Jiang Xudong
Lin, Dongli.
format Final Year Project
author Lin, Dongli.
author_sort Lin, Dongli.
title Recovery of the distorted barcodes for mobile applications
title_short Recovery of the distorted barcodes for mobile applications
title_full Recovery of the distorted barcodes for mobile applications
title_fullStr Recovery of the distorted barcodes for mobile applications
title_full_unstemmed Recovery of the distorted barcodes for mobile applications
title_sort recovery of the distorted barcodes for mobile applications
publishDate 2009
url http://hdl.handle.net/10356/17889
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