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Blind image separation based on exponentiated transmuted Weibull distribution
Faculty
Science
Year:
2016
Type of Publication:
ZU Hosted
Pages:
Authors:
Roshdy Mohamed Farouk AbdulHameed
Staff Zu Site
Abstract In Staff Site
Journal:
International Journal of Computer Science and Information Security (IJCSIS), International Journal of Computer Science and Information Security (IJCSIS),
Volume:
Keywords :
Blind image separation based , exponentiated transmuted
Abstract:
In recent years the processing of blind image separation has been investigated. As a result, a number of feature extraction algorithms for direct application of such image structures have been developed. For example, separation of mixed fingerprints found in any crime scene, in which a mixture of two or more fingerprints may be obtained, for identification, we have to separate them. In this paper, we have proposed a new technique for separating a multiple mixed images based on exponentiated transmuted Weibull distribution. To adaptively estimate the parameters of such score functions, an efficient method based on maximum likelihood and genetic algorithm will be used. We also calculate the accuracy of this proposed distribution and compare the algorithmic performance using the efficient approach with other previous generalized distributions. We find from the numerical results that the proposed distribution has flexibility and an efficient result.
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Roshdy Mohamed Farouk AbdulHameed, "Iris recognition based on elastic graph matching and Gabor wavelets", Elsevier, 2010
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Roshdy Mohamed Farouk AbdulHameed, "Iris matching using multi-dimensional artificial neural network", IET, 2010
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Roshdy Mohamed Farouk AbdulHameed, "Analytical analysis of image representation by their discrete wavelet transform", International Journal of Computer Science, 2008
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Roshdy Mohamed Farouk AbdulHameed, "Ultrasonic digital signal processing simulation in viscoelastic medium with generalized parametric function", Springer, 2012
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Roshdy Mohamed Farouk AbdulHameed, "Multiple interacting objects tracking based on generalized probabilistic distribution function", wulfenia, 2013
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