Detection of QR-Codes in Digital Images Based on Histogram Similarity

• Autorzy: Ciążyński, K. , Fabijańska, A.
• Języki publikacji: EN

Abstrakty

EN

This paper considers the problem of QR codes detection in digital images. In particular, the approach for detection of QR codes is proposed. The approach is based on histogram correlation between the reference image of QR code and the input image. In particular the input image is firstly divided into blocks. These are next used to build binary map of regions similar and dissimilar in terms of histogram to the image of QR code. On the binary map the morphological operations are next applied in order to remove outliers and identify the QR code. The results of applying the introduced approach to various images are presented and discussed. Different lighting conditions, image resolutions and orientations of QR codes are considered.

Słowa kluczowe

EN

bar code; augmented reality; algorithm

• Czasopismo: Image Processing & Communications
• Rocznik: 2015
• Tom: Vol. 20, no. 2
• Strony: 41--48
• Opis fizyczny: Bibliogr. 9 poz., rys., tab.

Twórcy

autor

Ciążyński, K.

• Łóź University of Technology, Institute of Applied Computer Science,

autor

Fabijańska, A.

• Łóź University of Technology, Institute of Applied Computer Science,

Bibliografia

• [1] -, (2006). Information technology – Automatic identification and data capture techniques – QR Code 2005 bar code symbology specification, ISO/IEC 18004:2006
• [2] Al-Khalifa, H. S. (2008). Utilizing QR code and mobile phones for blinds and visually impaired people (pp. 1065-1069). Springer Berlin Heidelberg
• [3] Belussi, L. F., Hirata, N. S. (2011). Fast QR code detection in arbitrarily acquired images. In Graphics, Patterns and Images (Sibgrapi), 2011 24th SIBGRAPI Conference on (pp. 281-288). IEEE
• [4] Gutierrez, F., Abud, M. A., Vera, F., Sanchez, J. A. (2013). Application of contextual QR codes to augmented reality technologies. In Electronics, Communications and Computing (CONIELECOMP), 2013 International Conference on (pp. 264-269). IEEE.
• [5] Ishak, I., Sidi, F., Affendey, L. S., Sani, N. F. M., Hamzah, A. S., Bawon, P. (2013). Mobile Plant Tagging System for Urban Forest Eco-Tourism Using QR Code. In Advanced Computer Science Applications and Technologies (ACSAT), 2013 International Conference on (pp. 37-41). IEEE.
• [6] Panyindee, C., Pintavirooj, C. (2013). QR codes application for reversible watermarking algorithm in biomedical images. In Biomedical Engineering International Conference (BMEiCON), 2013 6th (pp. 1-4). IEEE.
• [7] Park, H., Kim, T., Park, J. (2014). [Poster] QR code alteration for augmented reality interactions. In Mixed and Augmented Reality (ISMAR), 2014 IEEE International Symposium on (pp. 293-294). IEEE.
• [8] Sun, M., Fang, Z., Fu, L., Zhao, F. (2010, September). Identification of QR codes based on pattern recognition. In World Automation Congress (WAC), 2010 (pp. 397-401). IEEE.
• [9] Teng, C. H., Wu, B. S. (2012, September). Developing QR code based augmented reality using SIFT features. In Ubiquitous Intelligence & Computing and 9th International Conference on Autonomic & Trusted Computing (UIC/ATC), 2012 9th International Conference on (pp. 985-990). IEEE.

Identyfikatory

DOI

10.1515/ipc-2015-0033