Journal of Internet Computing and Services (인터넷정보학회논문지)

Korean Society for Internet Information (한국인터넷정보학회)
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Design and Implementation of Digital Jikin using Smartphone Application

  • Received : 2017.06.02
  • Accepted : 2017.10.28
  • Published : 2017.10.31
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Abstract

Due to the recent advances of IT industry, many companies and institutions have been used electronic documents rather than original paper copies. However, the characteristic of electronic document allows it to be readily damaged from proscribed copying, counterfeit, and falsification. These can cause the serious security problems for electronic documents. Conventional security methods for digital documents involve adding a separated image or marker, but these methods can reduce the readability of document. Therefore, we proposed a digital Jikin (Korean traditional stamp) which is normally used to identify the source or author of a document in asia. The proposed digital Jikin can preserve the readability of electronic document while protecting the document from proscribed copying, counterfeit, or falsification using image processing approach. In this paper, a digital Jikin application is designed and implemented under android platform and it converts the critical information of document onto the digital Jikin. The proposed digital Jikin contains important information in the boundary of Jikin not only about the author of documents or source, but also keywords, number of images, and many more. Therefore, the authenticity of document or whether the document has been altered or not by other person can be evaluated by the server. The proposed digital Jikin can be sent to a server through the wireless networks and can be stored using PHP and MySQL. We believe that the proposed method can offer the better and simple solution for strengthening the security of electronic document.

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References

  1. University Certpia, "http://certpia.com"
  2. Yong-Ri Piao, Seok-Tae Kim, "Digital Watermarking using Multi-resolution Characteristic of 2D Celluar Automata Transform," Journal of Korean Institute of Communications and Information Sciences, Vol. 34, No. 1, pp. 105-112, 2009.
  3. Chin-Ling Chen, Chin-Chang Chen, "A Verifiable and Traceable Secondhand Digital Media Market Protocol," KSII Transactions on Internet and Information Systems(TIIS), Vol. 5, No. 8, pp. 1472-1491, 2011. https://dx.doi.org/10.3837/tiis.2011.08.007
  4. Sun-Kyung Kang, Sang-Seol Lee, Sung-Tae Jung, "Development of a detection and recognition system for rectangular marker," Journal of the Korea Society of Computer and Information, Vol. 11, No. 4, pp. 97-107, 2006.
  5. I. Pitas, "Digital Image Processing schemes and Application," John Wiley and Sons, Inc, 2000.
  6. Martin Hirzer, "Marker Detection for Augmented Reality Applications," Seminar/Project Image Analysis Graz, 2008.
  7. J. Hershberger, J. Snoeyink, "Speeding up the Douglas Peucker line simplification algorithm," In Proc. 5th Intl Symp Spatial Data Handling, IGU Commissionon GIS, pp. 134-133, 1992.
  8. Woonggi Kim, Junchul Chun, "A Hybrid Approach of Efficient Facial Feature Detection and Tracking for Real-time Face Direction Estimation," Journal of Internet Computing and Services(JICS), Vol. 14, No. 1, pp. 117-124, 2013. https://dx.doi.org/10.7472/jksii.2013.14.6.117
  9. Amarmend, Eun-Chul Lee, Jung-Won Lee, Byeongjeong Lee, "Describing Activities to Verify Artifacts(Documents and Program) in Software R&D," Journal of Internet Computing and Services (JICS), Vol. 17, No. 2, pp. 39-47, 2016. https://dx.doi.org/10.7472/jksii.2016.17.2.39
  10. Smith, Alvy Ray, "Planar 2-pass texture mapping and warping," ACM SIGGRAPH Computer Graphics, Vol. 21, No, 4, pp. 263-272, 1987. https://dx.doi.org/10.1145/37401.37433
  11. Youngho Lee, Jongmyung Choi, "Texture Extraction from Video and Image Warping for AR Coloring Book," Computer Science and its Applications, Springer Berlin0 Heidelberg, pp. 361-365, 2014. https://doi.org/10.1007/978-3-662-45402-2_55
  12. Joo-Haeng Lee, "Geometric Method for Detection of Image Quadrilateral," Proceedings of the Society of CAD/CAM Conference, pp. 141-144, 2016.
  13. Trajkovic, Miroslav, Mark Hedley, "Fast corner detection," Image and vision computing Vol. 16. No. 2, pp. 75-87, 1998. https://doi.org/10.1016/S0262-8856(97)00056-5
  14. Wang, Han, Michael Brady, "Real-time corner detection algorithm for motion estimation," Image and vision computing Vol. 13. No. 9, pp. 695-703, 1995. https://doi.org/10.1016/0262-8856(95)98864-P
  15. Zheng, Zhiqiang, Han Wang, Eam Khwang Teoh, "Analysis of gray level corner detection," Pattern Recognition Letters, Vol. 20, No. 2, pp. 149-162, 1999. https://doi.org/10.1016/S0167-8655(98)00134-2