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Dey S.,Camellia Institute of Technology | Bhattacharyya S.,RCC Institute of Information Technology | Maulik U.,Jadavpur University
Swarm and Evolutionary Computation

In this paper, two meta-heuristics techniques have been employed to introduce two new quantum inspired meta-heuristic methods, namely quantum inspired genetic algorithm and quantum inspired particle swarm optimization for bi-level thresholding. The proposed methods use Otsu's method, Ramesh's method, Li's method, Shanbag's method and also correlation coefficient as evaluation functions to determine optimal threshold values of gray-level images. They exploit the trivial concepts of quantum computing such as qubits and superposition of states. These properties help to exhibit the feature of parallelism that in turn utilizes the time discreteness of quantum mechanical systems. The proposed methods have been compared with their classical counterparts and later with the quantum evolutionary algorithm (QEA) proposed by Han et al. to evaluate the performance among all participating algorithms for three test images. The optimal threshold value with the corresponding fitness value, standard deviation of fitness and finally the computational time of each method for each test image have been reported. The results prove that the proposed methods are time efficient while compared to their conventional counterparts. Another comparative study of the proposed methods with the quantum evolutionary algorithm (QEA) proposed by Han et al. also reveals the weaknesses of the latter. © 2013 Elsevier B.V. © 2014 Elsevier Inc. © 2013ElsevierB.V.Allrightsreserved. Source

Kundu A.,Camellia Institute of Technology
Proceedings of the 2010 International Conference on Signal and Image Processing, ICSIP 2010

Motion estimation is the most important component of any video coding standard. So development of an efficient algorithm for fast motion estimation is the basic need for video encoder design. Block based motion estimation algorithms are used for fast motion estimation as block matching algorithms eliminate the temporal redundancy present in any video sequence and use optimized search area to reduce computational time. In this paper I have reviewed existing block based motion estimation algorithms like exhaustive full search (FS), three step search (TSS), adaptive dual cross diamond hexagon search (ADCDHS) and performed a comparative analysis of their performance. I have also proposed a Modified Diamond Hexagon Search which will use reduced search area compare to existing TSS, DAHSA, and ADCDHS and in turn it will reduce computational time. Application of proposed algorithm for local motion analysis is also discussed in this paper. ©2010 IEEE. Source

In radiative transfer, the intensities of radiation from the bounding faces of a scattering atmosphere of finite optical thickness can be expressed in terms of Chandrasekhar's X- and Y-functions. The nonlinear nonhomogeneous coupled integral equations which the X- and Y-functions satisfy in the real plane are meromorphically extended to the complex plane to frame linear nonhomogeneous coupled singular integral equations. These singular integral equations are then transformed into nonhomogeneous Riemann-Hilbert problems using Plemelj's formulae. Solutions of those Riemann-Hilbert problems are obtained using the theory of linear singular integral equations. New forms of linear nonhomogeneous decoupled expressions are derived for X- and Y-functions in the complex plane and real plane. Solutions of these two expressions are obtained in terms of one known N-function and two new unknown functions N1- and N2- in the complex plane for both nonconservative and conservative cases. The N1- and N2-functions are expressed in terms of the known N-function using the theory of contour integration. The unknown constants are derived from the solutions of Fredholm integral equations of the second kind uniquely using the new linear decoupled constraints. The expressions for the H-function for a semi-infinite atmosphere are obtained as a limiting case. © Springer Science+Business Media B.V. 2009. Source

Pal D.,Camellia Institute of Technology
Asian Journal of Information Technology

The complexity of home networks has evolved to a greater level of sophistication and complicacy in the recent times comprising of heterogeneous components like at least two computers, web-enabled high-definition television sets, net-enabled blue ray disc players, iPods and many other such devices. Troubleshooting such a sophisticated smart home network in case of a malfunction by the novice end users seems to be very demanding. The study proposes a Smart Home Network Monitoring System that provides a centralized, general-purpose, automatic and convergent logging facility with the purpose to auto-detect and possibly correct all such failure issues by having a well-defined set of adaptive and incremental rule engine that needs to be applied to the entire network in general. Logging of all events that happened before trouble appeared may give a greater insight and hence help in providing an effective and permanent troubleshooting mechanism. This study also reports the initial experience of deploying such a facility. © Medwell Journals, 2012. Source

Bhattacharyya S.,University of Burdwan | Dey S.,Camellia Institute of Technology
Proceedings - 2011 International Conference on Computational Intelligence and Communication Systems, CICN 2011

A genetic algorithm inspired by the inherent features of parallelism and time discreteness exhibited by quantum mechanical systems, is presented in this article. The predominant interference operator in the proposed quantum inspired genetic algorithm (QIGA) is influenced by time averages of different random chaotic map models derived from the randomness of quantum mechanical systems. Subsequently, QIGA uses quantum inspired crossover and mutation on the trial solutions, followed by a quantum measurement on the intermediate states, to derive sought results. Application of QIGA to determine optimum threshold intensities is demonstrated on two real life gray level images. The efficacy of QIGA is adjudged w.r.t. a convex combination of two fuzzy thresholding evaluation metrics in a multiple criterion scenario. Comparative study of its performance with the classical counterpart indicates encouraging avenues. © 2011 IEEE. Source

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