• Journal of Navigation and Port Research
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• v.32 no.5
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• pp.355-361
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• 2008

Stereo matching is one of the most active research areas in computer vision. In this paper, we propose a stereo matching scheme using genetic algorithm for object depth recognition. The proposed approach considers the matching environment as an optimization problem and finds the optimal solution by using an evolutionary strategy. Accordingly, genetic operators are adapted for the circumstances of stereo matching. An individual is a disparity set. Horizontal pixel line of image is considered as a chromosome. A cost function is composed of certain constraints which are commonly used in stereo matching. Since the cost function consists of intensity, similarity and disparity smoothness, the matching process is considered at the same time in each generation. The LoG(Laplacian of Gaussian) edge is extracted and used in the determination of the chromosome. We validate our approach with experimental results on stereo images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1972-1978
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• 2010

AAM(Active Appearance Model) is one of the most effective ways to detect deformable 2D objects and is a kind of mathematical optimization methods. The cost function is a convex function because it is a least-square function, but the search space is not convex space so it is not guaranteed that a local minimum is the optimal solution. That is, if the initial value does not depart from around the global minimum, it converges to a local minimum, so it is difficult to detect face contour correctly. In this study, an AAM-based face tracking algorithm is proposed, which is robust to various lighting conditions and backgrounds. Eye detection is performed using SIFT and Genetic algorithm, the information of eye are used for AAM's initial matching information. Through experiments, it is verified that the proposed AAM-based face tracking method is more robust with respect to pose and background of face than the conventional basic AAM-based face tracking method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.84-91
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• 2006

In this paper, we present a new segmentation algorithm for color images based on mathematical morphology and a Gaussian mixture model(GMM). We use the morphological operations to determine the number of components in a mixture model and to detect their modes of each mixture component. Next, we have adopted the GMM to represent the probability distribution of color feature vectors and used the deterministic annealing expectation maximization (DAEM) algorithm to estimate the parameters of the GMM that represents the multi-colored objects statistically. Finally, we segment the color image by using posterior probability of each pixel computed from the GMM. The experimental results show that the morphological operation is efficient to determine a number of components and initial modes of each component in the mixture model. And also it shows that the proposed DAEM provides a global optimal solution for the parameter estimation in the mixture model and the natural color images are segmented efficiently by using the GMM with parameters estimated by morphological operations and the DAEM algorithm.

• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.677-682
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• 2004

In the present paper routing and wavelength assignment (RWA) in optical WDM networks is considered. Previous techniques based on the combination of integer linear programming and graph coloring are complex and require extensive use of heuristics. Such methods are mostly slow and sometimes impossible to get results due to infeasibility. An alternative approach applied to RWA employs on the greedy algorithm for obtaining the maximum edge disjoint paths. Even though this approach is fast, it produces a solution for any connection request, which is very far from the optimal utilization of wavelengths. We propose a novel algorithm, which is based on the maximum flow technique to obtain the maximum quantity of edge, disjoint paths. Here we compare the offered method with previous maximum edge disjoint paths algorithms ap plied to the RWA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.524-532
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• 2002

This paper reports that the Lambert W function applies to a non-iterative design of minimum mean square-error scalar quantizers for a Laplacian source. Specifically, it considers a non-iterative design algorithm for optimum quantizers for a Laplacian source; it finds that the solution of the recursive nonlinear equation in the non-iterative design is elegantly expressed in term of the principal branch of the Lambert W function in a closed form; and it proves that the non-iterative algorithm applies only to exponential or Laplacian sources. The contribution of the paper is in the reduction of the time needed for the design and the increased accuracy in resulting quantization points and thresholds, because the algorithm is non-iterative and the Lambert W function can be evaluated as accurately as desired. Also, numerical results show how optimal quantization distortion converges monotonically to the Panter-Dite constant and help derive an approximation formula for the key parameters of optimum quantizers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.3 no.2
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• pp.31-44
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• 1983

This paper applies an optimization algorithm for the elastic truss structures. The acceleration technique utilized in this study is the geometric programming method developed by the Operation Research or the applied methematics. The applicability and the efficiency of the algorithm applied in this study are tested for four different trusses. Test results show that the optimum solutions are obtained after only one or seven iterations which is very small compared with other techniques and no oscillation is needed for the convergency. Test rusults also show that the Geometric Programming Method is also effective algorithm for the convergency of the Optimum Solution in case of only being compared with the number of iteration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.344-351
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• 2016

In the point of view of a train operator, the main concern with a train operation is not only to maintain a time schedule, but also to decrease the energy consumption as much as possible. Generally for a manual drive, a train conductor controls the train acceleration and deceleration by controlling the notches not to exceed the regulation velocity by considering the given maximum velocity profile for an operation route. For this case, the guideline for a conductor is needed to choose the proper notches by applying the notch optimization so as to drive at the regulation velocity and minimize energy consumption simultaneously. In this paper, the real-time notch optimization plan is suggested using a genetic algorithm that optimizes the notches for the remaining route in real time when the event occurs that track information or regulation velocity profile of the remaining route changes during train operation as well as a normal operation situation. An energy saving effect and the convergence behavior of the optimal solution obtained was analyzed in a genetic algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.10
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• pp.654-663
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• 2014

Heterogeneous network (HetNet) with the various types of cells, e.g., with the different cell size and transmit power, has been introduced to improve the cell coverage and areal capacity in cellular mobile communication system. In this paper, we consider a practical situation in which all cells share the same wireless resource while some of them have a limited backhaul capacity. More specifically, we formularize a cell association problem that utilizes the minimum wireless resource while satisfying the quality of service (QoS) of all users in terms of their transmission time constraint, and propose a distributed algorithm to find the optimal solution. In the event of bottleneck at the backhaul link in some small cells, the proposed algorithm off-loads some users to the adjacent cell with the less congested backhaul capacity. Finally, we verify that the proposed algorithm supports the more numbers of users to satisfy the specified level of QoS than the conventional user association scheme under the limited access and backhaul capacities.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.120-127
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• 2011

Checkpointing is one of common methods of realizing fault-tolerance for real-time systems. This paper presents a scheme to determine checkpoint intervals using probabilistic optimization. The considered real-time systems comprises multiple tasks in which transient faults can happen with a Poisson distribution. Also, multi-tasks are scheduled by the non-preemptive Rate Monotonic (RM) algorithm. In this paper, we present an optimization problem where the probability of task completion is described by checkpoint numbers. The solution to this problem is the optimal set of checkpoint numbers and intervals that maximize the probability. The probability computation includes schedulability test for the non-preemptive RM algorithm with respect to given numbers of checkpoint re-execution. A case study is given to show the applicability of the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.2032-2041
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• 1998

In this work, we propose a novel bit allocation method that is to minimize overall distortions subject ot the bit rate constraint. We partition the original bitallocation problem into 'macroblock level bit allocation' problems that can be solved by conventional Lagrangian mutiplier methods and a 'frame level bit allocation' problem. To tackle the frame level problem, 'two-phase optimization' algorithm is used with iter-frame dependency model. While the existing approaches are almost impossible to find the macroblock-unit result for the moving picture coding system due to high computational complexity, the proposed algorithm can drastically reduce the computational loads by the problem partitioning and can obtain the result close to the optimal solution. Because the optimally allocated results can be used as a benchmark for bit allocation methods, the upper performance limit, or a basis for approximation method development, we expect that the proposed algorithm can be very useful for the bit allocation related works.