Applications of Barcode Images by Enhancing the Two-Dimensional Recognition Rate

Full Text (PDF, 379KB), PP.26-32

Views: 0 Downloads: 0


Jen-Yu Shieh 1,* Jia-Long Zhang 1 Yu-Ching Liao 1 Kun-Hsien Lin 1

1. Department of Electro-Optics Engineering, National Formosa University, Yunlin County, 632, Taiwan

* Corresponding author.


Received: 21 Apr. 2012 / Revised: 8 May 2012 / Accepted: 14 Jun. 2012 / Published: 28 Jul. 2012

Index Terms

Color image segmentation, Visible color difference, Region growing, Human color perception


The paper not only proposed the latest Two-Dimensional Barcodes Image-processing Module, but also captured the smallest camera screens (320 240) with different focal distances and tried to find out “Finder Pattern” for positioning images. Further, use CROBU (Conversion Ratio of Basic Unit) the thesis proposed to convert 2-D barcodes into 1-pixel ratio to match images before judging recognition rate of 2-D barcodes through matching. Normally speaking, 2-D barcodes are deciphered and recognized by software while the thesis recognizes 2-D barcodes and enhances implementation speed up to 10-cm accurate max. using image matching. The 2-D barcodes image-processing module the thesis proposed does capture and standardize image with complicated background or raw edge, which enhances 2-D barcodes recognition rate. The main point of this study is to construct a platform to manage or suggest nutrients human body needs. The Quick Response Code image of 2-D barcodes represents vitamin and calories information. 2-D barcodes taken instantly by MATLAB and CCD camera can be used to list nutrients from foods you eat recently and suggest what else you should eat for the purpose of health management.

Cite This Paper

Jen-Yu Shieh,Jia-Long Zhang,Yu-Ching Liao,Kun-Hsien Lin,"Applications of Barcode Images by Enhancing the Two-Dimensional Recognition Rate", IJIGSP, vol.4, no.7, pp.26-32, 2012. DOI: 10.5815/ijigsp.2012.07.03


[1]Functional Foods/Foods for Health Consumer Trending Survey, EXECUTIVE RESEARCH REPORT, International Food Information Council (IFIC), 2009.

[2]S.D. Drake, “Embracing Next-Generation Mobile Platforms to Solve Business Problems”, a Sybase White Paper, Oct 2008. Accessed 7/4/2009.

[3]Y.-H. Chang, C.-H. Chu, and M.-S. Chen., A General Scheme for Extracting QR Code from a non-uniform background in Camera Phones and Applications, Ninth IEEE International Symposium on Multimedia ,pp.123-130, Taichung, Taiwan, 2007.

[4]C.J. Ho, W.H Hsien, and G.-J. Jong., Multi-user Signals Combined with Quadratic Residue Code for Monitoring System, Eighth International Conference on Intelligent System Design and Application ,pp.100-103,Kaohsiung, Taiwan,2008.

[5]J.M. Su, Skewed QR Code Recognition on Handheld Device, Department of Computer Science and Information Engineering National Taipei University of Technology, Taiwan, 2007.

[6]C.Y. Lai, Extracting QR Code from a Non-uniform Background Image in Embedded Mobile Phones, Department of Communication Engineering National Taiwan University Taipei, Taiwan, 2007.

[7]E. Ohbuchi, H. Hanaizumi, L.A. Hock, Barcode readers using the camera device in mobile phones, Proceeding of IEEE 3rd International Conference on Cyberworlds, pp.260-265 ,Tokyo, Japan, 2004.

[8]Y.C. Lai, F.N. Han, Y.H. Yeh, A GPS Navigation System with QR Code Decoding and Friend Positioning in Smart Phones, 2nd International Conference on Education Technology and Computer (ICETC), Page V5-66 V5-70,Shanghai, 2010.

[9]S. Hend A.l. Khalifa, Utilizing QR Code and Mobile Phones for Blinds and Visually Impaired People, Computers Helping People with Special Needs Lecture Notes in Computer Science, Volume 5105/2008, Publisher: Springer, Pages:1065-1069, 2008.

[10]T.Y. Liu, T.H. Tan, Y.L. Chu, QR Code and Augmented Reality-Supported Mobile English Learning System, Volume: 5960, Publisher: Springer, Pages: 37-52, 2010.

[11]Y.H. Xue ,G.H. Tian, R.K. Li, H.T. Jiang, A new object search and recognition method based on artificial object mark in complex indoor environment, Intelligent Control and Automation (WCICA), 8th World Congress ,Page(s): 6648 – 6653, 2010.

[12]J. Matas , L. M. Soh , J. Kittler, Object Recognition Using A Tag, IEEE 1977 International Conference on Image Processing, vol.1 Page(s): 877 – 880, 1997.

[13]Rachid Hedjam , Reza Farrahi Moghaddam, Mohamed Cheriet, A spatially adaptive statistical method for the binarization of historical manuscripts and degraded document images, Pattern Recognition Volume 44, Issue 9, September, Pages 2184-2196, 2011.