• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1903-1906
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• 2003

This paper proposes an adaptive regularized noise smoothing algorithm for range image using the area decreasing flow method, which can preserve meaningful edges during the smoothing process. Although the area decreasing flow method can easily smooth Gaussian noise, it has two problems; ⅰ) it is not easy to remove impulsive noise from observed range data, and ⅱ) it is also difficult to remove noise near edge when the adaptive regularization is used. In the paper, therefore, the second smoothness constraint is addtionally incorporated into the existing regularization algorithm, which minimizes the difference between the median filtered data and the estimated data. As a result, the Proposed algorithm can effectively remove the noise of dense range data with edge preserving.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.529-535
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• 2004

Load forecasting is essential in the electricity market for the participants to manage the market efficiently and stably. A wide variety of techniques/algorithms for load forecasting has been reported in many literatures. These techniques are as follows: multiple linear regression, stochastic time series, general exponential smoothing, state space and Kalman filter, knowledge-based expert system approach (fuzzy method and artificial neural network). These techniques have improved the accuracy of the load forecasting. In recent 10 years, many researchers have focused on artificial neural network and fuzzy method for the load forecasting. In this paper, we propose an algorithm of a hybrid load forecasting method using fuzzy linear regression and general exponential smoothing and considering the sensitivities of the temperature. In order to consider the lower load of weekends and Monday than weekdays, fuzzy linear regression method is proposed. The temperature sensitivity is used to improve the accuracy of the load forecasting through the relation of the daily load and temperature. And the normal load of weekdays is easily forecasted by general exponential smoothing method. Test results show that the proposed algorithm improves the accuracy of the load forecasting in 1996.

• Journal of IKEEE
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• v.19 no.2
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• pp.244-253
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• 2015

Please This paper presents method of video stabilization based on detection and adaptive motion smoothing filtering of undesirable motion. The proposed algorithm consists of two stages: the detection of undesirable motion and smoothing filtering of detected undesired motion. To incorporate desired properties into the motion smoothing process, the local maximum and the local minimum are defined in a set composed of the parameters of accumulative global motion. Using the local information, the constraints on detecting undesirable motions are defined. Based on these constraints, the alpha parameter of the alpha-trimmed means filter is adjusted, so that the degree of motion smoothing in the reconstructed video sequence is controlled. The experimental results demonstrated the capability of the proposed algorithm.

• The KIPS Transactions:PartC
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• v.9C no.5
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• pp.679-686
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• 2002

The transmission of prerecorded and compressed video data without degradation of picture quality requires video servers to cope with large fluctuations in bandwidth requirement. Bandwidth smoothing techniques can reduce the burst of a variable-bit rate stream by prefetching data at a series of fixed rates and simplifying the allocation of resources in the video servers and the network. In this paper, the proposed smoothing algorithm results in the optimal transmission plans for (1) the smallest bandwidth requirements, (2) the minimum number of changes in transmission rate, and (3) the minimum amount of the server process overhead. The advantages of the proposed smoothing algorithm have been verified through the comparison with the existing smoothing algorithms in diverse environments.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.898-904
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• 1987

A new control algorithm using the VSS theory is developed for accurate trajectory control of robot manipulators. This paper focuses on the implementation of VSS controller with smoothing laws in the design of effective tracking control for robotic arms. The VSS controller for multi-linkage robot arm is realized using balance condition and its simplification which possesses powerful smoothing capability to reduce or even remove undesirable chattering and meanwhile keep the robust characteristic to reject system uncertainties. The design principle of selecting different smoothing methods, which aims at achieving trade-off between smoothing and robust behaviors while considering the actual system constraints, is also given and further confirmed through experimental results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.11C
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• pp.1112-1123
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• 2002

Providing a multimedia service requires efficient network bandwidth allocation scheduling. Typically, transmission of information with bursty characteristics, such as a video data stream, utilizes some type of smoothing technique that reduces the transmission rate fluctuation. While capable of a drastic reduction in the peak transmission rate, even the optimum smoothing algorithm proposed to date, however, is rather inadequate for multi-stream applications that share network bandwidth since such an algorithm has been designed and applied toward handling each independent stream. In this paper, we proposed an efficient bandwidth allocation algorithm that addresses these shortcomings. The proposed bandwidth allocation algorithm is divided into two steps, a static bandwidth allocation and a dynamic bandwidth allocation. In the former case, the peak rate reduction is achieved by maintaining the accumulated data in the user buffer at a high level, whereas the concept of real demand factor is employed to meet the needs of multi-stream bandwidth allocation in the latter case, Finally, the proposed algorithm's performance was verified with ExSpect 6.41, a Petri net simulation tool.

• The Journal of the Acoustical Society of Korea
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• v.10 no.3
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• pp.31-36
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• 1991

We propose an efficient pre-classification algorithm extracting candidate words to reduce the recognition time in a large-vocabulary recognition system and also propose the use of spectral and temporal smoothing of the observation probability to improve its classification performance. The proposed algorithm computes the coarse likelihood score for each word in a lexicon using the observation probabilities of speech spectra and duration information of recognition units. With the proposed approach we could reduce the computational amount by 74% with slight degradation of recognition accuracy in 1160-word recognition system based on the phoneme-level HMM. Also, we observed that the proposed coarse likelihood score computation algorithm is a good estimator of the likelihood score computed by the Viterbi algorithm.

• Journal of Digital Contents Society
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• v.8 no.1
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• pp.9-15
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• 2007

Smoothing is a transmission plan where variable rate video data is converted to a constant bit rate stream. Among them are CBA, MCBA, MVBA, e-PCRTT and others. e-PCRTT algorithm, which was improved from PCRTT, restricts the number of rate changes with fixed-size run. This causes unnecessary rate changes when run size is small and buffer size is large. In this paper, to overcome a shortcoming of e-PCRTT algorithm, a smoothing algorithm is proposed, which is improved from e-PCRTT, where a transmission rate transmits more intervalsl as possible. Experiments demonstrated that the proposed algorithm outperformed e-PCRTT algorithm. In order to show the performance, various evaluation factors were used such as the number of transmission rate changes, peak rate, transmission rate variability and so on.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3694-3702
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• 1999

OSL algorithm has an advantage that repeated algorithm is easily derived, even though penalty function which has a complicated transcendental function. In order to solve this problem, we suggested MPEMG algorithm. However, though this algorithm extend convergence rate of smoothing constant, it include the problem that is not faster than OSL algorithm in the convergence rate increasing penalized log-likelihood. Accordingly, in this paper, we will suggest SMOSLG digital image restoration algorithm which is fast in the convergence rate as well as extend convergence region of smoothing constant. And also we will study the usefulness of algorithm suggested through digital image simulation.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.236-245
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• 2008

Robust face recognition under various illumination environments is very difficult and needs to be accomplished for successful commercialization. In this paper, we propose an efficient illumination preprocessing method for face recognition. illumination preprocessing algorithm based on anisotropic smoothing is well known to be effective among illumination normalization methods but deteriorates the intensity contrast of the original image, and incurs less sharp edges. The proposed method in this paper improves the previous anisotropic smoothing based illumination normalization method so that it increases the intensity contrast and enhances the edges while diminishing effects of illumination. Due to the result of these improvements, face images preprocessed by the proposed illumination preprocessing method becomes to have more distinctive feature vectors(Gabor feature vectors). Through experiments of face recognition using Gabor jet similarity, the effectiveness of the proposed illumination preprocessing method is verified.