Measuring Object Dimensions and its Distances Based on Image Processing Technique by Analysis the Image Using Sony Camera

Authors :Huda M. Jawad1 & Tahseen A. Husain2
1Al-Mustansiriyah University, College of Science, Department of Physics, Baghdad, Iraq
2University of Raparin, College of Science, Department of Physics, Soleimani, Iraq

Abstract:  The measurement of object dimensions and its distance is essential for many technical applications. The purpose of this study was to find a suitable mathematical model in order to find an easy and accurate way to determine the object dimensions and its distance. This study was divided into two parts: the first one was to determine the dimensions of objects using a digital camera and a single laser pointer by placing those objects on black screen at different distances away from the camera then the second step was to determine the ranges of the objects using the images of two laser spots. Results show there is a relationship between different zoom and scale factor, and there is convergence and similarity between the experimental and theoretical values.

Keywords:  Image Processing, Object Range, Sony Camera, Laser Pointer


doi: 10.23918/eajse.v3i2p100


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References
Burger, W., & Burge, M.J. (2016). Digital image processing: an algorithmic introduction using Java.
Springer.

Dijk, J., van Eekeren, A.W., Schutte, K., & de Lange, D.J.J. (2007). Point target detection using
super-resolution reconstruction, Proc. of SPIE Vol, pp. 65660U-65661.
Duarte, F.J. (2008). Tunable Laser Applications. CRC press.
Ertico (2007). PReVENT project homepage. Retrieved from http://www.prevent-ip.org/status.
Forster, F. (2005). Real-time range imaging for human-machine interfaces. Retrieved from
https://mediatum.ub.tum.de/doc/601625/601625.pdf
Herald, S.M. (2008). Laser pointers restricted after attacks. Sydney Morning Herald.
Lymperis, D., Diamantis, A., Syrcos, G., & Karagiannis, S. (2007). Image processing algorithms for
a computer assisted allergy testing system. 3rd International Conference on Computational
Intelligence in Medicine and Healthcare, CIMED.
Mengel, P., & Wertheimer, R. (2007). D52.300.1 camera requirements and specifications. User
Cams project deliverable. Retrieved from http://www.prevent-ip.org/en/public
documents/deliverables/d523001 usercams general specifications.htm
Modrow, D., Laloni, C., Doemens, G., & Rigoll, G. (2007). 3d face scanning systems based on
invisible infrared coded light. Advances in Visual Computing, 521-530.
Nedev, S., & Ivanova, V.C. (2006). Web camera as a measuring tool in the undergraduate physics
laboratory. European Journal of Physics 27, 1213.
Oggier, T., Kaufmann, R., Lehmann, M., Buttgen, B., Neukom, S., Richter, M., Schweizer, M.,
Metzler, P., Lustenberger, F., & Blanc, N. (2005). Novel pixel architecture with inherent
background suppression for 3 D time-of-flight imaging, Proc. SPIE, pp. 1-8.
Rahi, M.F. (2010). Driver circuit construction using visible semiconductor laser for distance
measuremen. Al- Mustansiriyah University, College of Science, Dep. Physics.
Sachs, J. (1996). Digital image basics. Digital Light & Color. Retrieved from
http://www.dl-c.com/Temp/downloads/Whitepapers/Basics.pdf
Song, K.T., & Tang, W.H. (2000). Driver circuit construction using visible semiconductor laser for
distance measuremen. Graduate School of Information Systems” The University of
Electro-Communications Choufu-shi, Tokyo, JAPAN 182-8585, 2000.
fukuchi@megaUI.net.
Van Eekeren, A., Schutte, K., Dijk, J., De Lange, D., & Van Vliet, L. (2006). Super-resolution on
moving objects and background, Image Processing, 2006 IEEE International Conference
on. IEEE, pp. 2709-2712.
Van Eekeren, A.W.M., & Schutte,