IDENTIFIKASI BARCODE SATU DIMENSI MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION

In today�s modern society, almost every consumer product has a barcode label. Laser-based barcode scanners have become very sophisticated, but the camerabased scanners still has some problems. The scanner has a limited performance when dealing with images taken in difficult light conditions. Often...

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Main Authors: , SALMAN ALIAJI, , Drs. Agus Harjoko, M.sc., Ph.D
Format: Theses and Dissertations NonPeerReviewed
Published: [Yogyakarta] : Universitas Gadjah Mada 2012
Subjects:
ETD
Online Access:https://repository.ugm.ac.id/100111/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=56915
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spelling id-ugm-repo.1001112016-03-04T08:48:42Z https://repository.ugm.ac.id/100111/ IDENTIFIKASI BARCODE SATU DIMENSI MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION , SALMAN ALIAJI , Drs. Agus Harjoko, M.sc., Ph.D ETD In today�s modern society, almost every consumer product has a barcode label. Laser-based barcode scanners have become very sophisticated, but the camerabased scanners still has some problems. The scanner has a limited performance when dealing with images taken in difficult light conditions. Often the identification barcode with a camera-based scanners to be difficult because the process of shooting that is not true. It causes the resulting image has low quality, like a blurry picture, not focus or noise. ANN with high ability can be used to identify the barcode, but has many uses complex algorithms such as backpropagation. Barcode identification in this research consists of two main processes, namely the training process and the identification process. Training process is used to conduct training barcode character patterns. While the identification process consists of several stages starting from the process of image acquisition, conversion, locating barcode, scanline, normalization, testing and validation. The training process and testing process using neural networks with Learning Vector Quantization algorithm (LVQ). Based on the results of the comparison and testing that has been done, LVQ method can be used for identifying the barcode label image. Although it has not been able to surpass commercial barcode reader, but the proposed method has a fairly good degree of accuracy. From 72 images that have been tested, there are 53 images were identified correctly, so get the level of accuracy is 73.6%. [Yogyakarta] : Universitas Gadjah Mada 2012 Thesis NonPeerReviewed , SALMAN ALIAJI and , Drs. Agus Harjoko, M.sc., Ph.D (2012) IDENTIFIKASI BARCODE SATU DIMENSI MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=56915
institution Universitas Gadjah Mada
building UGM Library
country Indonesia
collection Repository Civitas UGM
topic ETD
spellingShingle ETD
, SALMAN ALIAJI
, Drs. Agus Harjoko, M.sc., Ph.D
IDENTIFIKASI BARCODE SATU DIMENSI MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION
description In today�s modern society, almost every consumer product has a barcode label. Laser-based barcode scanners have become very sophisticated, but the camerabased scanners still has some problems. The scanner has a limited performance when dealing with images taken in difficult light conditions. Often the identification barcode with a camera-based scanners to be difficult because the process of shooting that is not true. It causes the resulting image has low quality, like a blurry picture, not focus or noise. ANN with high ability can be used to identify the barcode, but has many uses complex algorithms such as backpropagation. Barcode identification in this research consists of two main processes, namely the training process and the identification process. Training process is used to conduct training barcode character patterns. While the identification process consists of several stages starting from the process of image acquisition, conversion, locating barcode, scanline, normalization, testing and validation. The training process and testing process using neural networks with Learning Vector Quantization algorithm (LVQ). Based on the results of the comparison and testing that has been done, LVQ method can be used for identifying the barcode label image. Although it has not been able to surpass commercial barcode reader, but the proposed method has a fairly good degree of accuracy. From 72 images that have been tested, there are 53 images were identified correctly, so get the level of accuracy is 73.6%.
format Theses and Dissertations
NonPeerReviewed
author , SALMAN ALIAJI
, Drs. Agus Harjoko, M.sc., Ph.D
author_facet , SALMAN ALIAJI
, Drs. Agus Harjoko, M.sc., Ph.D
author_sort , SALMAN ALIAJI
title IDENTIFIKASI BARCODE SATU DIMENSI MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION
title_short IDENTIFIKASI BARCODE SATU DIMENSI MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION
title_full IDENTIFIKASI BARCODE SATU DIMENSI MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION
title_fullStr IDENTIFIKASI BARCODE SATU DIMENSI MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION
title_full_unstemmed IDENTIFIKASI BARCODE SATU DIMENSI MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION
title_sort identifikasi barcode satu dimensi menggunakan metode learning vector quantization
publisher [Yogyakarta] : Universitas Gadjah Mada
publishDate 2012
url https://repository.ugm.ac.id/100111/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=56915
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