Journal of Theoretical and Applied Information Technology 15 th October 2018. Vol.96. No 19 © 2005 – ongoing JATIT & LLS ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 6633 EVALUATION OF A FUZZY 3D COLOR QR CODE DECODER 1 Bakri Badawi, 2 TEH NORANIS MOHD ARIS 3 Norwati Mustapha, 4 Noridayu Manshor 1,2,3,4 Department of Computer Science, Faculty of Computer Science and Information Technology, 43400 UPM Serdang, Selangor, Malaysia E-mail: 1 bakri.info@gmail.com, 2 nuranis@upm.edu.my (corresponding author) 3 norwati@upm.edu.my, 4 ayu@upm.edu.my ABSTRACT 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. Keywords Fuzzy, QR code, QR code version, Color QR code, Decoder 1. INTRODUCTION QR code convert any type of digital data into transferable images consisting of thousands of bits per image, which can be displayed on the screen or printed, and then captured by smartphone camera to recover the information [1, 2, 3]. Due of this feature QR codes are being used everywhere in marketing and network security applications such as business cards, storefront displays, letter stamps, movie posters, shortcuts to URL links, information tracking products, a means to store contact information for easy transfer, admission tickets or boarding passes, etc. [1, 3, 4, 5, 6]. QR code is a special type of 2D barcode. QR code has many features like 360 degree rotation, error correction, and larger data capacity that can be encoded within it [1, 4, 7, 8]. QR code can hold data size up to 10 times higher than normal barcode. However, there is also limitation of QR code. Since the maximum data size for black and white (B/W) QR code is 10208 bits [1, 4, 5], the QR code is unable to encode simple files like PDF files, Word documents, PowerPoint slide show. Having QR- Code with larger capacity will facilitate many modern applications and make transferring data easier. Many research works have been implemented to overcome the size limitation and color lamination for QR code using various techniques such as diffuse reflection [19], color reference [22] and colour multiplexing with metadata [6]. In this paper, we compare the success rate for these techniques with the success rate using our proposed fuzzy technique. This paper consists of 7 sections. Section 2 is about color QR code. Section 3 explains barcodes types. Section 4 provides facts on the benefits of having larger QR code size. Section 5 reviews the related research works. Section 6 discusses on the results of the experiments and finally section 7 is the conclusion and future works.