Modeling in An Optical Tomography System Using Different Pixel Configurations

Authors

  • Siti Zarina Mohd Muji Department of Computer Engineering, Faculty of Electric and Electrical Engineering, UniversitiTun Hussein Onn Malaysia, 86400 Parit Raja, BatuPahat, Johor, Malaysia
  • Yap Sin Fah Department of Computer Engineering, Faculty of Electric and Electrical Engineering, UniversitiTun Hussein Onn Malaysia, 86400 Parit Raja, BatuPahat, Johor, Malaysia
  • Randy Justin Karim Department of Computer Engineering, Faculty of Electric and Electrical Engineering, UniversitiTun Hussein Onn Malaysia, 86400 Parit Raja, BatuPahat, Johor, Malaysia
  • Ruzairi Abdul Rahim Process Tomography and Instrumentation Engineering Research Group (PROTOM-i), Infocomm Research Alliance, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Norhidayati Podari Department of Computer Engineering, Faculty of Electric and Electrical Engineering, UniversitiTun Hussein Onn Malaysia, 86400 Parit Raja, BatuPahat, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v64.2137

Keywords:

Pixel resolution, reconstructed image, simulation, infra-red sensor, accurate image

Abstract

Pixel resolution is important in forming an image. The aim of this paper is to compare the reconstructed image of an array infra-red sensor by using different configurations of pixels. The different number of objects will be tested in this simulation. The dimension of pixel that uses to reconstruct the image is important to form a clear and accurate image.

References

Paul Suetens. 2002. Fundamentals of Medical Imaging. Publicis Corporate Publishing, Erlangen. 66–68.

Mohd Muji, S. Z., Abdul Rahim, R., Fazalul Rahiman, M. H., Sahlan, S., Abdul Shaib, M. F., Puspanathan, M. J., Mohamad, E. J. 2011. Optical Tomography: A Review on Sensor Array, Projection Arrangemnet and Image Reconstruction Algorithm. International Journal of Innovative Computing, Information and Control. 7(7): 3839–3856.

Dyakowski, T. 1995. Tomography in a Process System. In Williams, R. A and Beck, M. S. 1st ed. Process Tomography: Principles, Techniques and Applications. London: Butterworth-Heinemann Ltd. 13–36.

Macal, C. M. 2005. Model Verification and Validation. Workshop on Threat Anticipation: Social Science Methods and Models. University of Chicago.

Jackson, R. G. 1995. The Development of Optical Systems for Process Imaging. In Williams, R. A and Beck, M. S. 1st ed. Process Tomography: Principles, Techniques and Applications. London: Butterworth- Heinemann Ltd. 167–179.

R. Abdul Rahim. S. Z. Mohd. Muji. January 2013. Optical Tomography : Image Improvement using Mix Projection of Parallel and Fan Beam Mode. Measurement Journal (ISSN: 0263-2241) Elsevier Science. 46: 1970–1978.

Downloads

Published

2013-09-15

Issue

Vol. 64 No. 5: Special Edition

Section

Science and Engineering

License

Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.

How to Cite

Modeling in An Optical Tomography System Using Different Pixel Configurations. (2013). Jurnal Teknologi (Sciences & Engineering), 64(5). https://doi.org/10.11113/jt.v64.2137