Optimization of the Jakim halal logo placement on qr code using enhanced genetic algorithm

A logo placed on Quick Response (QR) code provides additional aesthetic value and visual information to the user. Visual quality of the embedded logo is an important criterion besides success in QR code readability. Unfortunately, most work placed a logo on QR code with low embedded data capacity. T...

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Main Author: Rohani, Fuaad
Format: Thesis
Language:English
Published: 2018
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/76064/1/FK%202018%20147%20IR.pdf
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spelling my-upm-ir.760642019-11-29T03:39:33Z Optimization of the Jakim halal logo placement on qr code using enhanced genetic algorithm 2018-05 Rohani, Fuaad A logo placed on Quick Response (QR) code provides additional aesthetic value and visual information to the user. Visual quality of the embedded logo is an important criterion besides success in QR code readability. Unfortunately, most work placed a logo on QR code with low embedded data capacity. Therefore, Jabatan Kemajuan Islam Malaysia (JAKIM) halal premises information is used to represent high data capacity. The thesis proposed a method to place a logo on top of the QR code, embedded with high data capacity, using Genetic Algorithm (GA) search technique to find appropriate size and location so the QR code can be decoded by various QR code decoders. Pad codewords modification technique is used to minimize the error introduced by the logo while three QR code decoders are used to achieve high probability of decode feasibility. A fitness function has been formulated to determine the appropriate size and location of the logo. A total of 3949 samples retrieved from JAKIM public access database was segregated into six groups based on the amount of information that could be embedded in the QR code, wherein 10% of the items from each group were used as samples for data generation. From the experiments, logo size about 69 to 76 pixels which covered about 5.39% to 7.16% of the QR code area can be used for all items in the respective group without decoding failure compared to 2% currently used in JAKIM Halal tag. The module pixel error in the QR code is found to be less than 4.25%. The logo placement system had successfully avoided error correction modules and control patterns, simultaneously, the placement location of the logo is maintained within the QR code area. The proposed work has been compared to GA-based technique, module modification technique and Simulated Annealing technique related to QR code readability, embedded logo visual quality and high embedded data capacity. As a conclusion, the system can successfully find a set of logo size and location on a QR code embedded with high data capacity that does not affect the QR code readability and can be decoded by various decoders with 100% accuracy. QR codes - Case studies Food - Religious aspects - Islam 2018-05 Thesis http://psasir.upm.edu.my/id/eprint/76064/ http://psasir.upm.edu.my/id/eprint/76064/1/FK%202018%20147%20IR.pdf text en public masters Universiti Putra Malaysia QR codes - Case studies Food - Religious aspects - Islam
institution Universiti Putra Malaysia
collection PSAS Institutional Repository
language English
topic QR codes - Case studies
Food - Religious aspects - Islam

spellingShingle QR codes - Case studies
Food - Religious aspects - Islam

Rohani, Fuaad
Optimization of the Jakim halal logo placement on qr code using enhanced genetic algorithm
description A logo placed on Quick Response (QR) code provides additional aesthetic value and visual information to the user. Visual quality of the embedded logo is an important criterion besides success in QR code readability. Unfortunately, most work placed a logo on QR code with low embedded data capacity. Therefore, Jabatan Kemajuan Islam Malaysia (JAKIM) halal premises information is used to represent high data capacity. The thesis proposed a method to place a logo on top of the QR code, embedded with high data capacity, using Genetic Algorithm (GA) search technique to find appropriate size and location so the QR code can be decoded by various QR code decoders. Pad codewords modification technique is used to minimize the error introduced by the logo while three QR code decoders are used to achieve high probability of decode feasibility. A fitness function has been formulated to determine the appropriate size and location of the logo. A total of 3949 samples retrieved from JAKIM public access database was segregated into six groups based on the amount of information that could be embedded in the QR code, wherein 10% of the items from each group were used as samples for data generation. From the experiments, logo size about 69 to 76 pixels which covered about 5.39% to 7.16% of the QR code area can be used for all items in the respective group without decoding failure compared to 2% currently used in JAKIM Halal tag. The module pixel error in the QR code is found to be less than 4.25%. The logo placement system had successfully avoided error correction modules and control patterns, simultaneously, the placement location of the logo is maintained within the QR code area. The proposed work has been compared to GA-based technique, module modification technique and Simulated Annealing technique related to QR code readability, embedded logo visual quality and high embedded data capacity. As a conclusion, the system can successfully find a set of logo size and location on a QR code embedded with high data capacity that does not affect the QR code readability and can be decoded by various decoders with 100% accuracy.
format Thesis
qualification_level Master's degree
author Rohani, Fuaad
author_facet Rohani, Fuaad
author_sort Rohani, Fuaad
title Optimization of the Jakim halal logo placement on qr code using enhanced genetic algorithm
title_short Optimization of the Jakim halal logo placement on qr code using enhanced genetic algorithm
title_full Optimization of the Jakim halal logo placement on qr code using enhanced genetic algorithm
title_fullStr Optimization of the Jakim halal logo placement on qr code using enhanced genetic algorithm
title_full_unstemmed Optimization of the Jakim halal logo placement on qr code using enhanced genetic algorithm
title_sort optimization of the jakim halal logo placement on qr code using enhanced genetic algorithm
granting_institution Universiti Putra Malaysia
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/76064/1/FK%202018%20147%20IR.pdf
_version_ 1747813110546169856