Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
A Social Tagging Recommendation Model Based on Improved Artificial Fish Swarm Algorithm and Tensor Decomposition Read chapter Read first chapter

2018 | OriginalPaper | Chapter

A New Aesthetic QR Code Algorithm Based on Salient Region Detection and SPBVM

Authors : Li Li, Yanyun Li, Bing Wang, Jianfeng Lu, Shanqing Zhang, Wenqiang Yuan, Saijiao Wang, Chin-Chen Chang

Published in: Security with Intelligent Computing and Big-data Services

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Many aesthetic QR code algorithms have been proposed. In this paper, a new aesthetic QR code algorithm, based on salient region detection and Selectable Positive Basis Vector Matrix (SPBVM), is proposed. Firstly, the complexity of texture features are added to calculate the saliency values, based on the existing salient region detection algorithm. According to the saliency map, the important area of the image is preserved for the subsequent beautification operation. Then, the appropriate basis vectors are selected by using the proposed SPBVM according to the acquired salient region, and the salient region is displayed completely by XOR operation which is performed by the generated original QR code and the selected basis vectors. Finally, the aesthetic QR code is obtained by combining the background image and the original QR code. The results show that the pro-posed algorithm can produce more accurate salient area and have more pleasant visual effect.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Research on the Nearest Neighbor Representation Classification Algorithm in Feature Space
next chapter Compact Cat Swarm Optimization Algorithm
Literature
1.
2.
3.
4.
Ono, S., Morinaga, K., Nakayama, S.: Two-dimensional barcode decoration based on real-coded genetic algorithm. In: Evolutionary Computation, pp. 1068–1073. IEEE (2008)
5.
Baharav, Z., Kakarala, R.: Visually significant QR codes: image blending and statistical analysis. In: IEEE International Conference on Multimedia and Expo, pp. 1–6. IEEE (2013)
6.
Li, L., Qiu, J., Lu, J., et al.: An aesthetic QR code solution based on error correction mechanism. J. Syst. Softw. 116(C), 85–94 (2016)CrossRef
7.
Fujita, K., Kuribayashi, M., Morii, M.: Expansion of image displayable area in design QR code and its applications. In: Proceedings of the Forum on Information Technology Papers, vol. 10(4), pp. 517–520 (2011)
8.
Lin, S.S., Hu, M.C., Lee, C.H., et al.: Efficient QR code beautification with high quality visual content. IEEE Trans. Multimedia 17(9), 1515–1524 (2015)CrossRef
9.
Garateguy, G.J., Arce, G.R., Lau, D.L., et al.: QR images: optimized image embedding in QR codes. IEEE Trans. Image Process. 23(7), 2842–2853 (2014)MathSciNetCrossRefMATH
10.
Xu, X.Y.: Research on digital rights protection methods in digital publish, pp. 27–32. Hangzhou Dianzi University, Hangzhou (2016)
11.
Cheng, M.M., Mitra, N.J., Huang, X., et al.: Global contrast based salient region detection. IEEE Trans. Pattern Anal. Mach. Intell. 37(3), 569–582 (2015)CrossRef
12.
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn., pp. 534–540. Publishing House of Electronics Industry, Beijing (2011). (in Chinese)
13.
Wang, X., Georganas, N.D.: GLCM texture based fractal method for evaluating fabric surface roughness. In: Canadian Conference on Electrical and Computer Engineering, 2009, CCECE 2009, pp. 104–107. IEEE (2009)
14.
Haralick, R.M., Shanmugam, K.: Textural features for image classification. IEEE Trans. Syst. Man Cybern. 3(6), 610–621 (1973)CrossRef
15.
Kavitha, C., Rao, B.P., Govardhan, A.: Image retrieval based on color and texture features of the image sub-blocks. Int. J. Comput. Appl. 15(7), 33–37 (2011)
16.
Chen, Y.Q., Duan, J., Zhu, Y., Qian, X.F., Xiao, B.: Research on the image complexity based on texture features. Chin. Opt. 8(3), 407–414 (2015). (in Chinese)CrossRef
17.
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62–66 (1979)MathSciNetCrossRef
Metadata
Title
A New Aesthetic QR Code Algorithm Based on Salient Region Detection and SPBVM
Authors
Li Li
Yanyun Li
Bing Wang
Jianfeng Lu
Shanqing Zhang
Wenqiang Yuan
Saijiao Wang
Chin-Chen Chang
Copyright Year
2018
Book
Security with Intelligent Computing and Big-data Services

Print ISBN: 978-3-319-76450-4

Electronic ISBN: 978-3-319-76451-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-76451-1_3

Premium Partner

    Image Credits