UUM Electronic Theses and Dissertation
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Using RGB colour combination in coloured quick response (QR) code algorithm to enhance QR code capacity

Azizi, Abas (2018) Using RGB colour combination in coloured quick response (QR) code algorithm to enhance QR code capacity. PhD. thesis, Universiti Utara Malaysia.

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A Quick Response (QR) Code is a two-dimensional barcode that stores characters and can be read by any smartphone camera. The QR code has the capability to encode various data formats and languages; nevertheless, existing black and white QR code offers limited data storage. Even though there exist research on coloured QR Code to increase the storage capacity, requirement for larger data capacity by end user keep increasing. Hence, this thesis proposes a coloured QR Code algorithm which utilizes RGB colour combination to allow a larger data storage. The proposed algorithm integrates the use of compression, multiplexing, and multilayer techniques in encoding and decoding the QR code. Furthermore, it also introduces a partial encoding/decoding algorithm that allows the stored data to be manipulated. The algorithm that includes encoding and decoding processes is based on the red, green, and blue (RGB) colour techniques, which are used to create high capacity coloured QR code. This is realised in the experiments that store American Standard Code for Information Interchange (ASCII) characters. The ASCII text characters are used as an input and performance is measured by the number of characters that can be stored in a single black and white QR code version 40 (i.e. the benchmark) and also the coloured QR code. Other experiment metrics include percentage of missing characters, number of produced QR code, and elapsed time to create the QR code. Simulation results indicate that the proposed algorithm stores 29 times more characters than the black and white QR code and 9 times more than other coloured QR code. Hence, this shows that the coloured QR Code has the potential of becoming a useful mini-data storage as it does not rely on internet connection.

Item Type: Thesis (PhD.)
Supervisor : Yusof, Yuhanis and Kabir Ahmad, Fauzana
Item ID: 7470
Uncontrolled Keywords: Quick Response Code, Barcode, Information retrieval, Data storage; RGB colours.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Awang Had Salleh Graduate School of Arts & Sciences
Date Deposited: 04 Nov 2019 06:34
Last Modified: 04 Nov 2019 06:34
Department: Awang Had Salleh Graduate School of Arts and Sciences
Name: Yusof, Yuhanis and Kabir Ahmad, Fauzana
URI: https://etd.uum.edu.my/id/eprint/7470

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