Image edge detection using the hidden Markov model based on normal distribution with optimum expectation
Journal Title: International Research Journal of Applied and Basic Sciences - Year 2013, Vol 6, Issue 2
Abstract
THE HIDDEN MARKOV METHOD IS A ROBUST MODEL WHICH IS EMPLOYED IN VARIOUS FIELDS OF SCIENCE. ALTHOUGH IT HAS FREQUENTLY BEEN USED IN EDGE DETECTION THE WAVELET TRANSFORMATION HAS ALWAYS BEEN INCLUDED IN THE PROCESS. IN THIS PAPER,WE MODELED THE HIDDEN MARKOV METHOD BASED ON THE NORMAL DISTRIBUTION FOR IMAGE EDGE DETECTION (WITHOUT USING THE WAVELET TRANSFORMATION). THE ESTIMATION OF THE INCLUDED PARAMETERS WILL BE PRESENTED BY USING THE EM ALGORITHM FOLLOWED BY THE HIDDEN STATES, WHICH ARE CONSIDERED AS EDGESDETERMINED BY THE VITERBI ALGORITHM. FINALLY, WE WILL COMPARE OUR PROPOSED ALGORITHM WITH THAT OF CANNY AND OTHER ALGORITHMS WHICH ARE BASED ON THE HIDDEN MARKOV MODEL AND THE WAVELET TRANSFORMATION.
Authors and Affiliations
Hassan Sharghi gallejoog| Department of Statistics, Ardabil branch, Islamic Azad University, Ardabil, Iran, Reza Hashemi| Dept. of Statistics, Razi University, Kermanshah, Iran, Mehdi Rajabi| Department of Mathematics Ardabil branch, Islamic Azad University, Ardabil, Iran, email: mhd_rajabi@yahoo.com
Keywords
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