Implementasi Pengenalan Multiple Marker untuk Sistem Augmented Reality

Authors

  • Steven Febrian Harijanto Program Studi Teknik Informatika
  • Liliana - Program Studi Teknik Informatika
  • Kartika Gunadi Program Studi Teknik Informatika

Abstract

Making mockups for display to investors often requires a very high cost, manufacture mock floater if deemed there are less suitable in the making. To overcome this age often the designers will re-create the mock-scale model if it is not in accordance with the wishes of investors. But the problem that arises is the purchase of an expensive tool visual examples, so it is not efficient in generating cost manufacturing maket.

To overcome this, invented a visualization application mockups city park by using markers made of paper, so that the cost of making these mockups cheap, compared with money must be spent to buy equipment such as, trees, park benches, etc. Users can also add mockups according to keingginannya, can add objects that are free on the Internet, then choose a marker in accordance with his wishes, the User can print the even own mockups that will be used.

To make the visualization process is carried out mock-long process ranging from changing color to gray, change the color to black and white, edge detection, square detecting, matching the template to print the object desired dimensions. Through the test results, it was found that the result object that is displayed on the screen is in conformity with the position marker, the downside of this process is that the process that takes a long time rendering and 3D printing process object that still has texture and recognizable marker must rectangular.

References

[1] Akhmad Afissunani, Akuwan saleh, M. Hasbi Assidiqi. 2014. Multi Marker Augmented Reality untuk Aplikasi Magic Book.

[2] Kadir, Abdul. 2013. Dasar Pengolahan Citra Digital dengan Delphi. Yogyakarta: Penerbit Andi.

[3] Li, Z., Wong, K.H., Gong, Y. dan Chang M.Y. 2011. A Method for Movable Projector Keystone Correction. IEEE Transaction on Multimedia, Vol. 13, No. 1, February 2011.

[4] Surampalli, G.P. 2012. An Analysis of Skin Pixel Detection using Diffrenet Skin Color Extracction Techniques. International Journal of Computer Applications, Vol. 54, No. 17, September 2012.

[5] Zhou, P., Ye, W., Xia Y., & Wang, Q. 2011. An Improved Canny Algorithm for Edge Detection. Journal of Computional Information Systems, 7(5): 1516-1523, May 2011.

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Published

2015-01-31

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Section

Articles