• Vol 2, No 1 (2011)
  • Electrical, Electronics, and Computer Engineering

Identification of Signatures Transmitted over Rayleigh Fading Channel by Using HMM and RLE

Djamhari Sirat, Arman D. Diponegoro, Leni N. Hidayati, Filbert H. Juwono


Publish at : 01 Jan 2011 - 00:00
IJtech : IJtech Vol 2, No 1 (2011)
DOI : https://doi.org/10.14716/ijtech.v2i1.46

Cite this article as:
Sirat, D.., Diponegoro, A.D.., & Hidayati, .L.N..& Juwono, F.H.. 2017. Identification of Signatures Transmitted over Rayleigh Fading Channel by Using HMM and RLE. International Journal of Technology. Volume 2(1), pp.56-64
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Djamhari Sirat Department of Electrical Engineering, Faculty of Engineering Universitas Indonesia, Depok 16424, Indonesia
Arman D. Diponegoro Department of Electrical Engineering, Faculty of Engineering Universitas Indonesia, Depok 16424, Indonesia
Leni N. Hidayati Department of Electrical Engineering, Faculty of Engineering Universitas Indonesia, Depok 16424, Indonesia
Filbert H. Juwono Department of Electrical Engineering, Faculty of Engineering Universitas Indonesia, Depok 16424, Indonesia
Email to Corresponding Author

Abstract

The Hidden Markov Model (HMM) is a frequently used tool in scientific research for recognizing pattern. This study discusses signature recognition using HMM where the signature image is transmitted from the remote station to the headquarter office by wireless because the remote station was not provided by the original signature as a reference. Generally, the transmission of radio communication has been corrupted with Additive White Gaussian Noise (AWGN) over the Rayleigh fading channel. To reduce the number of bits in the bitstream, the signal prior to transmission was compressed by means of run-length encoding (RLE), also known as source coding. The signature image detected from the receiver was processed in the computer using the HMM. The successful rate of recognition was 0-36% without compression and 60-76%with compression.

Hidden Markov Model (HMM), Rayleigh fading; Run-Length Encoding (RLE)

References

Anonym, 2005. Two Dimensional Voronoi Diagram, [accessed on 20 April 2010].

Frejlichowski, D. & Lisaj, A., 2008. New Method of the Radar Images Compression for the Needs of Navigation in Marine Traffic, In: Proceedings of Radar Symposium, IEEE, pp 1-4.

Gonzales, R. & Woods, R., 1992. Digital Image Processing, USA: Addison Wesley Publishing Co.

Hou, W., Xiufen Y., Kejun W., 2004. A Survey of Off-line Signature Verification, In: Proceedings of the 2004 International Conference on Intelligent Mechatronics and Automation, August 2004, Chengdu, China.

Rabiner, L. R., 1989. A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition Proceedings, IEEE 77(2), 257-286.

Rabiner, L. R. & Juang, B. H., 1993. Fundamental of Speech Recognition, Englewood Cliffs, N.J.: Prentice Hall.

Wada, N & S.Hangai, 2007. HMM based Signature Identification System Robust to Changed of Signature with Time, IEEE Workshop on Automatic Identification Advanced Technologies, pp. 238-241.

Zhang, H. & A. Gulliver, 2009. A Channel Selective Approach to Wireless Image Transmission Over Fading Channels, Proceedings of IEEE Pacific Rim Conference on Communication, Computers and Signal Processing, pp. 720-724.