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The new method of Extraction and Analysis of Non-linear Features for face recognition Ali Mahdavi Hormat; Karim Faez; Zeynab Shokoohi; Mohammad Zaher Karimi
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 6: December 2012
Publisher : Institute of Advanced Engineering and Science

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Abstract

In this paper, we introduce the new method of Extraction and Analysis of Non-linear Features (EANF) for face recognition based on extraction and analysis of nonlinear features i.e. Locality Preserving Analysis. In our proposed algorithm, EANF removes disadvantages such as the length of search space, different sizes and qualities of imagees due to various conditions of imaging time that has led to problems in the previous algorithms and removes the disadvantages of ELPDA methods (local neighborhood separator analysis) using the Scatter matrix in the form of a between-class scatter that this matrix introduces and displayes the nearest neighbors to K of the outer class by the samples. In addition, another advantage of EANF is high-speed in the face recognition through miniaturizing the size of feature matrix by NLPCA (Non-Linear Locality Preserving Analysis). Finally, the results of tests on FERET Dataset show the impact of the proposed method on the face recognition.DOI:http://dx.doi.org/10.11591/ijece.v2i6.1773
A Method of Steganography – P Message With Q Coefficient (SPMQC) Zeinab Famili; Karim Faez; Abbas Fadavi
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 2: April 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

In this paper, we are going to propose a method for Steganography- which is based on deceiving χ2 algorithm. Since the cover image coefficients and stego image coefficients histograms have significant differences for purposes of statistical properties, statistical analysis of χ2-test reveals the existence of hidden messages inside stego image. We are introducing an idea for hiding messages in the cover image. It causes that DCT (Discrete Cosine Transforms) coefficient histogram not to have remarkable modification before and after embedding message. As a result, identifying the hidden message inside an image is impossible for an eavesdropper through χ2 -test. In this paper, we are proposing a better method with developing this algorithm. In fact, the capacity and the security of embedding messages increase extremely.DOI:http://dx.doi.org/10.11591/ijece.v3i2.2011
The Effect of Rearrangement of the Most Incompatible Particle on Increase of Convergence Speed of PSO Abbas Fadavi; Karim Faez
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 2: April 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

This article presents a new method for increasing the speed of Particle Swarm Optimization (PSO) method. The particle swarm is an optimization method that was inspired by collective movement of birds and fish looking for food. This method is composed of a group of particles: each particle tries to move in one direction that the best individual and best group of particles occur in that direction. Different articles tried to expand PSO so that global optimization is gained in less time. One of the problems of this model that occurs in most cases is falling of particles in local optimum. By finding the most incompatible particle and its rearrangement in the searching space, we increase convergence speed in some considered methods. Different tests of this method in standard searching space demonstrated that this method takes account of suitable function of increasing the convergece speed of particles.DOI:http://dx.doi.org/10.11591/ijece.v3i2.2026