Thresholding analysis on barcode image

The barcode systems are widely used in industry includes education, military, business, food and etc. The use of image processing on barcode reader is a way of extending the application to the normal user as most of today’s mobile phone is camera equipped. The only problem with the phone's came...

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Main Author:	Omar, Norsyira Zuraiza
Format:	Thesis
Published:	2010
Subjects:	TK Electrical engineering Electronics Nuclear engineering
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id	my-utm-ep.27028
record_format	uketd_dc
spelling	my-utm-ep.270282017-08-20T08:15:31Z Thresholding analysis on barcode image 2010 Omar, Norsyira Zuraiza TK Electrical engineering. Electronics Nuclear engineering The barcode systems are widely used in industry includes education, military, business, food and etc. The use of image processing on barcode reader is a way of extending the application to the normal user as most of today’s mobile phone is camera equipped. The only problem with the phone's camera is that the captured image is at low quality. This will affect the process of decoding the barcode. One of the processes is thresholding where the original image will be converted into black and white image. Thus, in this project, analysis on a few existing techniques is done as there are many techniques that have been developed for the thresholding. Then, die best thresholding technique is identified such that it is able to overcome the low quality image. The analysis is based on global and local thresholding for both Otsu’s method and GLCM with entropy technique. For global thresholding, window size of 640x480 is used while window size of 5x5, 10x10 and 20x20 is used for local thresholding. In the analysis, GLCM size is limited to 8, 16 and 32 with spatial distance of 1, 2 and 3. Other than that, the entire offset angle (0, 45, 90 and 135) is considered in this analysis and the threshold level for GLCM is determined by local, joint and global entropy. The result has shown that the best thresholding technique for low quality image is the thresholding that is based on GLCM. 2010 Thesis http://eprints.utm.my/id/eprint/27028/ masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Omar, Norsyira Zuraiza Thresholding analysis on barcode image
description	The barcode systems are widely used in industry includes education, military, business, food and etc. The use of image processing on barcode reader is a way of extending the application to the normal user as most of today’s mobile phone is camera equipped. The only problem with the phone's camera is that the captured image is at low quality. This will affect the process of decoding the barcode. One of the processes is thresholding where the original image will be converted into black and white image. Thus, in this project, analysis on a few existing techniques is done as there are many techniques that have been developed for the thresholding. Then, die best thresholding technique is identified such that it is able to overcome the low quality image. The analysis is based on global and local thresholding for both Otsu’s method and GLCM with entropy technique. For global thresholding, window size of 640x480 is used while window size of 5x5, 10x10 and 20x20 is used for local thresholding. In the analysis, GLCM size is limited to 8, 16 and 32 with spatial distance of 1, 2 and 3. Other than that, the entire offset angle (0, 45, 90 and 135) is considered in this analysis and the threshold level for GLCM is determined by local, joint and global entropy. The result has shown that the best thresholding technique for low quality image is the thresholding that is based on GLCM.
format	Thesis
qualification_level	Master's degree
author	Omar, Norsyira Zuraiza
author_facet	Omar, Norsyira Zuraiza
author_sort	Omar, Norsyira Zuraiza
title	Thresholding analysis on barcode image
title_short	Thresholding analysis on barcode image
title_full	Thresholding analysis on barcode image
title_fullStr	Thresholding analysis on barcode image
title_full_unstemmed	Thresholding analysis on barcode image
title_sort	thresholding analysis on barcode image
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2010
_version_	1747815569938186240

Thresholding analysis on barcode image

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