Evaluation of a fuzzy 3D color QR code decoder
This paper is an extension of our previous work on color QR code decoder using fuzzy logic. The input is the color QR codes with four versions which are version 3, 13, 14 and 17. These QR code versions are converted to black and white. Then, the QR codes are detected using an open source library nam...
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Little Lion Scientific
2018
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my.upm.eprints.726282020-11-16T09:18:46Z http://psasir.upm.edu.my/id/eprint/72628/ Evaluation of a fuzzy 3D color QR code decoder Badawi, Bakri Mohd Aris, Teh Noranis Mustapha, Norwati Manshor, Noridayu This paper is an extension of our previous work on color QR code decoder using fuzzy logic. The input is the color QR codes with four versions which are version 3, 13, 14 and 17. These QR code versions are converted to black and white. Then, the QR codes are detected using an open source library named as Zing. Next, the color QR code is retrieved by mapping the black and white QR code with the color image. This is followed by enhancing the color QR code using fuzzy logic. After that the QR code is split into three QR codes, red, green and blue. Each of the color is decoded to get the original file text file. We made a comparison on the success rate for our decoder with other existing decoder. We take in consideration number of color used, camera resolution, QR code version, and QR code error correction level. The comparison with other research work show that by using fuzzy logic improves the decoding success rate up to 93.33% using the same parameter from other research work. Little Lion Scientific 2018-10 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/72628/1/Evaluation%20of%20a%20fuzzy%203D%20color%20QR%20code%20decoder.pdf Badawi, Bakri and Mohd Aris, Teh Noranis and Mustapha, Norwati and Manshor, Noridayu (2018) Evaluation of a fuzzy 3D color QR code decoder. Journal of Theoretical and Applied Information Technology, 96 (19). 6633 - 6644. ISSN 1992-8645; ESSN: 1817-3195 http://www.jatit.org/volumes/ninetysix19.php |
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This paper is an extension of our previous work on color QR code decoder using fuzzy logic. The input is the color QR codes with four versions which are version 3, 13, 14 and 17. These QR code versions are converted to black and white. Then, the QR codes are detected using an open source library named as Zing. Next, the color QR code is retrieved by mapping the black and white QR code with the color image. This is followed by enhancing the color QR code using fuzzy logic. After that the QR code is split into three QR codes, red, green and blue. Each of the color is decoded to get the original file text file. We made a comparison on the success rate for our decoder with other existing decoder. We take in consideration number of color used, camera resolution, QR code version, and QR code error correction level. The comparison with other research work show that by using fuzzy logic improves the decoding success rate up to 93.33% using the same parameter from other research work. |
format |
Article |
author |
Badawi, Bakri Mohd Aris, Teh Noranis Mustapha, Norwati Manshor, Noridayu |
spellingShingle |
Badawi, Bakri Mohd Aris, Teh Noranis Mustapha, Norwati Manshor, Noridayu Evaluation of a fuzzy 3D color QR code decoder |
author_facet |
Badawi, Bakri Mohd Aris, Teh Noranis Mustapha, Norwati Manshor, Noridayu |
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Badawi, Bakri |
title |
Evaluation of a fuzzy 3D color QR code decoder |
title_short |
Evaluation of a fuzzy 3D color QR code decoder |
title_full |
Evaluation of a fuzzy 3D color QR code decoder |
title_fullStr |
Evaluation of a fuzzy 3D color QR code decoder |
title_full_unstemmed |
Evaluation of a fuzzy 3D color QR code decoder |
title_sort |
evaluation of a fuzzy 3d color qr code decoder |
publisher |
Little Lion Scientific |
publishDate |
2018 |
url |
http://psasir.upm.edu.my/id/eprint/72628/1/Evaluation%20of%20a%20fuzzy%203D%20color%20QR%20code%20decoder.pdf http://psasir.upm.edu.my/id/eprint/72628/ http://www.jatit.org/volumes/ninetysix19.php |
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