Halal food recognition system using barcode

With the steady growth and affordability of webeam, more applications technology is necessary. Nowadays the industry technology began to pay more attention to barcode applications for domestic users need. This thesis describes a. webcam support application for Muslims to identify the Halal status...

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Bibliographic Details
Main Author: Nor Emilia Zetty, Khairudin
Format: Undergraduates Project Papers
Language:English
Published: 2010
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/2627/
http://umpir.ump.edu.my/id/eprint/2627/
http://umpir.ump.edu.my/id/eprint/2627/1/NOR_EMILIA_ZETTY_BTE_KHAIRUDIN.PDF
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Summary:With the steady growth and affordability of webeam, more applications technology is necessary. Nowadays the industry technology began to pay more attention to barcode applications for domestic users need. This thesis describes a. webcam support application for Muslims to identify the Halal status (prepared in accordance to Islamic law) of the product. The barcode image is using several images preprocessing technique in order to extract the bat-code into database and also barcode recognition process. Halal Food Recognition System Using Barcode is a low cost barcode reader, which was developed by using a simple webcam as the input device. Barcodes are a class of the simplest printed patterns that can be reliably recognized by a computer. These codes, consist of sequence of parallel, light and dark stripes printed on papers. This is a real time application and that requires good processing power. This is the main reason for using the language MatLab for the development of the Halal Food Recognition System Using Barcode. The webcam application is an economical and effective way to speed up the .Halal verification process. This thesis discusses the barcode concept and its applications in consumer product industry. The experimental results obtained have system able to shown that recognition rates of 68% have been achieved. The result also revealed that the technique is robust and invariant to rotation. For future research and development can be done to improve the percentage of recognition so that zero error recognition is achieved.