• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.9
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• pp.764-774
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• 1990

In this paper, make a study on comparison of adaptive filters for predictor characteristics that transversal, lattice, and joint process lattice filter is using the LMS algorithm that is simple structure and pracotical application is easy. The theoical background and structure of each adaptive filters exhibit for practical design. Adaptive convergence condition for optimal weight vector and optimal reflection coefficient make clear, and it is also shown through computer simulation. The error signals and noise characteristics of these filters make a comparative study. In view of the results, joint process lattice filter is shown that most superior characteristic in these adaptie filters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.652-657
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• 2009

This paper proposes an adaptive noise suppression system based on human auditory model to enhance speech signal that is degraded by various background noises. The proposed system detects voiced, unvoiced and silence sections for each frame and implements an adaptive auditory process, then reduces the noise speech signal using a neural network including amplitude component and phase component. Based on measuring signal-to-noise ratios, experiments confirm that the proposed system is effective for speech signal that is degraded by various noises.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.766-770
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• 2010

In this paper, we present an effective covariance tracking algorithm based on adaptive size changing of tracking window. Recent researches have advocated the use of a covariance matrix of object image features for tracking objects instead of the conventional histogram object models used in popular algorithms. But, according to the general covariance tracking algorithm, it can not deal with the scale changes of the moving objects. The scale of the moving object often changes in various tracking environment and the tracking window(or object kernel) has to be adapted accordingly. In addition, the covariance matrix of moving objects should be adaptively updated considering of the tracking window size. We provide a solution to this problem by segmenting the moving object from the background pixels of the tracking window. Therefore, we can improve the tracking performance of the covariance tracking method. Our several simulations prove the effectiveness of the proposed method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.84-91
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• 2001

In this study, the adaptive analysis procedure of crack propagation based on the element-free Galerkin(EFG) method is presented. The adaptivity analysis in quasi-static crack propagation is achieved by adding and/or removing the node along the background integration cell that are refined or recovered according to the estimated error. These errors are obtained basically by calculating the difference between the values of the projected stresses and original EFG stresses. To evaluate the performance of proposed adaptive procedure, the crack propagation behavior is investigated for several examples. The results of these examples show the efficiency and accuracy of proposed scheme in crack propagation analysis.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.452-459
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• 1999

In this study, error estimates using the stress projecting scheme and adaptive nodal generation procedure in the element-free Galerkin(EFG) method are proposed. The essence of proposed error estimates is to use the difference between the values of the projected stress and these given directly by the EFG solution. The stress projection can be obtained simply by taking product of shape function based on a different domain of influence with the stresses at nodes. An adaptive procedure based on error estimates is discussed in this paper. By use of background integration cell, adding node scheme at high error norm area is proposed. To demonstrate the performance of proposed scheme, the convergence behavior is investigated for several examples

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.5
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• pp.324-326
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• 2005

An adaptive Chunk algorithm is newly devised and a collaborative streaming is designed for high quality multimedia streaming service under time varying traffic conditions. An LMS based prediction filter is used to compensate the effect of time varying background traffic of the WAN. The underflow is generated for the $20\~28\%$ of the data stored in the central server by applying the FARIMA(Fractional Autoregressive Integrated Moving Average) traffic modeling method. The proposed algorithm is tested with the MPEG-2 video files and compensates $71\~85\%$ of central stream underflow.

• Proceedings of the IEEK Conference
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• summer
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• pp.438-441
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• 2004

Image binarization using a global threshold value [3] performs at high speed, but usually results in undesired binary images when the source images are of poor quality. In such cases, adaptive local thresholding algorithms [1][2][3] are used to obtain better results, and the algorithm proposed by A.E.Savekis which chooses local threshold using fore­ground and background clustering [1] is one of the best thresholding algorithms. However, this algorithm runs slowly due to its re-computing threshold value of each central pixel in a local window MxM. In this paper, we present a dynamic programming approach for the step of calculating local threshold value that reduces many redundant computations and improves the execution speed significantly. Experiments show that our proposal improvement runs more ten times faster than the original algorithm.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.409-418
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• 2003

Object tracking in video is one of subject that computer vision and several practical application field have interest in several years. This paper proposes real time object tracking and face region extraction method that can be applied to security and supervisory system field. For this, in limited environment that camera is fixed and there is seldom change of background image, proposed method detects position of object and traces motion using difference between input image and background image. The system creates adaptive background image and extracts pixels in object using line scan method for more stable object extraction. The real time object tracking is possible through establishment of MBR(Minimum Bounding Rectangle) using extracted pixels. Also, effectiveness for security and supervisory system is improved due to extract face region in established MBR. And through an experiment, the system shows fast real time object tracking under limited environment.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1132-1137
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• 2011

In this paper, we propose Modified Multi CAMShift Algorithm(Modified Multi Continuously Adaptive Mean Shift Algorithm) that extracts skin color area and tracks several human body parts for real-time human tracking system. Skin color area is extracted by filtering input image in predefined RGB value range. These areas are initial search windows of hands and face for tracking. Gaussian background model prevents search window expending because it restricts skin color area. Also when occluding between these areas, we give more weights in occlusion area and move mass center of target area in color probability distribution image. As result, the proposed algorithm performs better than the original CAMShift approach in multiple object tracking and even when occluding of objects with similar colors.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.37-45
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• 2007

We propose an adaptive image enhancement method for epigraphic images, which is based on local statistics. Local statistics of the image are utilized for adaptive realization of the enhancement, that controls the contribution of the smoothing or sharpening paths. Image contrast enhancement occurs in details and noises are suppressed in smooth areas. For modeling the epigraphic image, pre~process is achieved by HSDI(Hanzi squeezed digital image). We have calculated the local statistics from this HSDI model. Application of this approach to HSDI has shown that processing not only smooths the background areas but also improves the subtle variations of edges, so that the word regions can be enhanced. Experimental results show that the proposed algorithm has better performance than the conventional image enhancement ones.