• Journal of Korea Multimedia Society
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• v.9 no.10
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• pp.1266-1275
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• 2006

In this paper, we propose a real-lime face detection and tracking algorithm using AdaBoost(Adaptive Boosting) algorithm. The proposed algorithm consists of two levels such as the face detection and the face tracking. First, the face detection used the eight-wavelet feature models which ate very simple. Each feature model applied to variable size and position, and then create initial feature set. The intial feature set and the training images which were consisted of face images, non-face images used the AdaBoost algorithm. The basic principal of the AdaBoost algorithm is to create final strong classifier joining linearly weak classifiers. In the training of the AdaBoost algorithm, we propose SAT(Summed-Area Table) method. Face tracking becomes accomplished at real-time using the position information and the size information of detected face, and it is extended view region dynamically using the fan-Tilt camera. We are setting to move center of the detected face to center of the Image. The experiment results were amply satisfied with the computational efficiency and the detection rates. In real-time application using Pan-Tilt camera, the detecter runs at about 12 frames per second.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.600-608
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• 2014

In this paper, CABAC H/W module is developed using co-design method. After entire H.264/AVC encoder was developed with C using reference SW(JM), CABAC H/W IP is developed as a block in H.264/AVC encoder. Context modeller of CABAC is included on the hardware to update the changed value during binary encoding, which enables the efficient usage of memory and the efficient design of I/O stream. Hardware IP is co-operated with the reference software JM of H.264/AVC, and executed on Virtex-4 FX60 FPGA on ML410 board. Functional simulation is done using Modelsim. Compared with existing H/W module of CABAC with register-level design, the development time is reduced greatly and software engineer can design H/W module more easily. As a result, the used amount of slice in CABAC is less than 1/3 of that of CAVLC module. The proposed co-design method is useful to provide hardware accelerator in need of speed-up of high efficient video encoder in embedded system.

• Journal of KIISE:Information Networking
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• v.31 no.3
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• pp.305-313
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• 2004

The use of a cache for a storing and processing of Web object is becoming larger. Also, many studies for efficient management of storing scope on cache are performed actively. Web caching technique have many differences with traditional techniques. Particularly, a heterogeneity of Web object which is a processing unit of Web caching and a variation of Web object reference characteristic with time are the important causes to decrease performance of existing techniques. In this study, We proposed the ACASH which was new web caching technique. As ACASH divided and managed Web object and a cache scope with a heterogeneity, It can reduced a heterogeneity variation of an object. Also, it is reflecting a variation of object reference characteristics with time adaptively. In the experiment, We verified that the performance of ACASH was improved than existing techniques on the two experiment model which considered a heterogeneity of an object.

• Journal of KIISE:Information Networking
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• v.32 no.2
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• pp.134-146
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• 2005

Research about QoS in the ad-hoc networks for stable service of various applications has been needed as the expectation about the realization of the ad-hoc networks grows bigger. Existing researches about QoS in the ad-hoc network had the problems which can not guarantee the quantitative services or create the overhead. In this paper, we propose a novel algorithm of QFAN(QoS Framework for Ad-hoc Networks) the framework to resolve such problems and considered application of the proposed algorithm into the ad-hoc networks. Our model can guarantee the minimum bandwidth of the real-time traffic as minimized the overhead. And, disproportionate distribution of bandwidth problem can resolve by the proposed algorithm through the fair share between real-time traffic and best-effort traffic about available bandwidth. We design both the TiRe(Tiny Reservation) and the ADR(Adaptive Drop Rate) control algorithm to apply the proposed QFAN. Using simulation, we confirm fair share of available bandwidth between real-time traffic and best-effort traffic as guarantee minimum required bandwidth of real-time traffic.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.18-25
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• 2011

In a manufacturing process of metal coins, surface defects of coins are manually detected. This paper describes an new method for detecting surface defects of metal coins on a moving conveyor belt using image processing. This method consists of multiple procedures: segmentation of a coin from the background, alignment of the coin to the model, projection of the aligned coin to the best eigen image space, and detection of defects by comparison of the projection error with an adaptive threshold. In these procedures, the alignement and the projection are newly developed in this paper for the detection of coin surface defects. For alignment, we use the histogram of the segmented coin, which converts two-dimensional image alignment to one-dimensional alignment. The projection reduces the intensity variation of the coin image caused by illumination and coin rotation change. For projection, we build multiple eigen image spaces and choose the best eigen space using estimated coin direction. Since each eigen space consists of a small number of eigen image vectors, we can implement the projection in real- time.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.800-804
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• 2005

This paper presents a fuzzy learning rule which is the fuzzified version of LVQ(Learning Vector Quantization). This fuzzy learning rule 3 uses fuzzy learning rates. instead of the traditional learning rates. LVQ uses the same learning rate regardless of correctness of classification. But, the new fuzzy learning rule uses the different learning rates depending on whether classification is correct or not. The new fuzzy learning rule is integrated into the improved IAFC(Integrated Adaptive Fuzzy Clustering) neural network. The improved IAFC neural network is both stable and plastic. The iris data set is used to compare the performance of the supervised IAFC neural network 3 with the performance of backprogation neural network. The results show that the supervised IAFC neural network 3 is better than backpropagation neural network.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.5
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• pp.105-118
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• 2006

Zara and Limited Brands in the fashion industry are two leading companies that satisfy the clients' needs and the trend of fashion. The agile organizations which response to the change of business environment or adaptive enterprises which monitor the customer's desires have been studied over the long time in the academic world. Recently these management concepts have been extended to the Real-Time Enterprise. In this paper how to implement the RTE in the fashion industry is suggested. To implement the RTE, the end-to-end process should be continuously operated without delays. Also, the three main attributes of RTE, -visibility, intelligence, and agility-should be achieved. Further more based on the cyclone model and the RTE attributes, important issues to be considered for the successful RTE implementation are discussed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.12
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• pp.856-864
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• 2019

The weapon-target assignment (WTA) problem is a matter of effectively allocating weapons to a number of threats. The WTA in a rapidly changing dynamic environment of engagement must take into account both of properties of the threat and the weapon and the effect of the previous decision. We propose a method of applying the Greedy Randomized Adaptive Search Procedure (GRASP) algorithm, a kind of meta-heuristic method, to derive optimal solution for a dynamic WTA problem. Firstly, we define a dynamic WTA problem and formulate a mathematical model for applying the algorithm. For the purpose of the assignment strategy, the objective function is defined and time-varying constraints are considered. The dynamic WTA problem is then solved by applying the GRASP algorithm. The optimal solution characteristics of the formalized dynamic WTA problem are analyzed through the simulation, and the algorithm performance is verified via the Monte-Carlo simulation.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.18-26
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• 2010

Many personalized services that provide users with adaptive information according to users' preferences have been researched and developed. Push services are especially expected to be more economic impact because push services satisfy user's potential needs even if the user does not require anything. In this paper, we propose Semantic Web approach in order to enhance the performance of push services. Our approach provides infrastructure to recommend contents based on semantic association by enabling information of contents and user preferences to be described on service-specific ontologies that reflect features of each service. In addition, our approach can recommend users with adaptive information based on information represented in our description model. Our approach enables information of contents and user preferences to be described with rich expressiveness, and it provides semantic interoperability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8C
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• pp.795-802
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• 2003

It is very important to construct statistical model in order to exactly estimate the signal variance from a noisy image. In order to estimate variance, information of neighboring region is used generally. The size of neighbor region is varied according to the regional characteristics of image. More accurate estimation of edge variance is due to smaller region of neighbor, on the other hands, larger region of neighbor is used to estimate the variance of flat region. By using estimated variance of original image, in general, Wiener filter is constructed, and it is applied to the noisy image. In this paper, we propose a new method for determining the range of neighbors to estimate the variance in wavelet domain. Firstly, a significance map is constructed using the parent-child relationship of wavelet domain. Based on the number of the significant wavelet coefficients, the range of neighbors is determined and then the variance of the original signal is estimated using ML(maximum likelihood method. Experimental results show that the proposed method yields better results than conventional methods for image denoising.