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An Android Business Card Reader Based on Google Vision: Design and Evaluation

  • Nguyen Hoang ThuanEmail author
  • Dinh Thanh Nhan
  • Lam Thanh Toan
  • Nguyen Xuan Ha Giang
  • Quoc Bao Truong
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 298)

Abstract

Business cards have been widely used to greet business professionals and exchange contact information. However, the current paper-based way to manage business cards impedes their effective usage, leading to a need for digitalising and extracting business card information. This paper aims to design a business card reader (BCR) application for Android devices. Based on Google vision library, the application digitalises and extracts business card information. We evaluate the application on a dataset of 170 business cards. The results show that the application can digitalise business cards and extract contact information with 88.4% of accuracy. We then further conduct a comparative analysis of our application and other commercial BCR applications. Based on the results, the paper suggests several recommendations for future research.

Keywords

Business card reader Android Design science Experiment 

Notes

Acknowledgement

We would like to thank Phi Thi Ngoc Minh for helping us taking business card pictures and compare business card data and data extracted by the application.

References

  1. 1.
    Hing, V., Khoo, H.K.: Business card reader with augmented reality engine integration. In: Ibrahim, H., Iqbal, S., Teoh, S.S., Mustaffa, M.T. (eds.) 9th International Conference on Robotic, Vision, Signal Processing and Power Applications. LNEE, vol. 398, pp. 219–227. Springer, Singapore (2017).  https://doi.org/10.1007/978-981-10-1721-6_24CrossRefGoogle Scholar
  2. 2.
    Dangiwa, B.A., Kumar, S.S.: A business card reader application for iOS devices based on Tesseract. In: 2018 International Conference on Signal Processing and Information Security (ICSPIS). IEEE (2018)Google Scholar
  3. 3.
    Lin, L., Tan, C.L.: Text extraction from name cards using neural network. In: Proceedings of 2005 IEEE International Joint Conference on Neural Networks. IEEE (2005)Google Scholar
  4. 4.
    Madan Kumar, C., Brindha, M.: Text extraction from business cards and classification of extracted text into predefined classes. Int. J. Comput. Intell. IoT 2(3), 595–602 (2019)Google Scholar
  5. 5.
    Mollah, A.F., et al.: Text/graphics separation for business card images for mobile devices. In: IAPR International Workshop on Graphics Recognition, pp. 263–270 (2009)Google Scholar
  6. 6.
    Hung, P.D., Linh, D.Q.: Implementing an android application for automatic Vietnamese business card recognition. Pattern Recogn. Image Anal. 29(1), 156–166 (2019)CrossRefGoogle Scholar
  7. 7.
    Mollah, A.F., Basu, S., Nasipuri, M.: Text detection from camera captured images using a novel fuzzy-based technique. In: 2012 Third International Conference on Emerging Applications of Information Technology. IEEE (2012)Google Scholar
  8. 8.
    Mollah, A.F., et al.: Text region extraction from business card images for mobile devices. In: Information Technology and Business Intelligence (2009)Google Scholar
  9. 9.
    Duy, N.: Xây dựng ứng dụng nhật diện danh thiếp trên Android. Can Tho University: in Vietnamese, Bachelor thesis (2017)Google Scholar
  10. 10.
    Đat, N.T.: Ứng dụng nhật diện danh thiếp tiếng Việt trên Android. Da Lat University: in Vietnamese (2018)Google Scholar
  11. 11.
  12. 12.
    Arthur. Android Image Cropper, 2016 June 2019. https://github.com/ArthurHub/Android-Image-Cropper
  13. 13.
    Hevner, A., Chatterjee, S.: Design Research in Information Systems: Theory and Practice. Integrated Series in Information Systems, vol. 22. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-1-4419-5653-8. Ed. R. Sharda and S. Voß
  14. 14.
    Hevner, A., et al.: Design science in information systems research. MIS Q. 28(1), 75–105 (2004)CrossRefGoogle Scholar
  15. 15.
    Thuan, N.H., Drechsler, A., Antunes, P.: Construction of design science research questions. Commun. Assoc. Inf. Syst. 44(1), 332–363 (2019)Google Scholar
  16. 16.
    Saiga, H., et al.: An OCR system for business cards. In: Proceedings of 2nd International Conference on Document Analysis and Recognition (ICDAR 1993). IEEE (1993)Google Scholar
  17. 17.
    Luo, X.-P., Li, J., Zhen, L.-X.: Design and implementation of a card reader based on build-in camera. In: Proceedings of the 17th International Conference on Pattern Recognition (ICPR). IEEE (2004)Google Scholar
  18. 18.
    Holsapple, C.W.: DSS architecture and types. In: Burstein, F., Holsapple, C.W. (eds.) Handbook on Decision Support Systems 1, pp. 163–189. Springer, Heidelberg (2008).  https://doi.org/10.1007/978-3-540-48713-5_9
  19. 19.
    Thuan, N.H.: Business Process Crowdsourcing: Concept, Ontology and Decision Support. Progress in IS. Springer, Heidelberg (2019).  https://doi.org/10.1007/978-3-319-91391-9. Ed. C. Rauscher
  20. 20.
    Chandrasekhar, V., et al.: Dataset: Stanford Mobile Visual Search Dataset, V. Research Datasets for Image, and Multimedia Systems Group at Stanford, Editor. Stanford (2013)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • Nguyen Hoang Thuan
    • 1
    Email author
  • Dinh Thanh Nhan
    • 1
  • Lam Thanh Toan
    • 1
  • Nguyen Xuan Ha Giang
    • 1
  • Quoc Bao Truong
    • 2
  1. 1.Can Tho University of TechnologyCan Tho CityVietnam
  2. 2.College of Engineering TechnologyCan Tho UniversityCan Tho CityVietnam

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