• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1455-1464
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• 2006

In this paper, we propose an adaptive image enhancement algorithm. The proposed algorithm is classified with the MIE technique for intensity enhancement of input image and MSE techniques for saturation enhancement. The MIE technique is proposed to control the gamut mapping problem and a sudden change in image-brightness while Luminance signal is processing, The MSE techniques are proposed to control de-saturation or over-saturation while chrominance signal is processing. The proposed algorithm is focused on processing preference color for human vision in order to generate better image quality than the algorithms focused on processing uniformly to whole images, This algorithm can be applied to a monitor, TV and other display devices for high quality image.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.173-178
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• 2005

This paper focuses on the use of the virtual dialog system whose aim is to build more convenient living environments. In order to realize this, the main emphasis of the paper lies on the description of the multimedia signal processing on the basis of the technologies such as speech recognition, speech synthesis, video, or sensor signal processing. For essential modules of the dialog system, we incorporated the real-time speech recognizer based on HM-Net(Hidden Markov Network) as well as speech synthesis into the overall system. In addition, we adopted the real-time motion detector based on the changes of brightness in pixels, as well as the touch sensor that was used to start system. In experimental evaluation, the results showed that the proposed system was relatively easy to use for controlling electric appliances while sitting in a sofa, even though the performance of the system was not better than the simulation results owing to the noisy environments.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.391-399
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• 2018

In this paper, we construct and compare various guitar chord classification systems using perceptron neural network and convolutional neural network without pre-processing other than Fourier transform to identify the optimal chord classification system. Conventional guitar chord classification schemes use, for better feature extraction, computationally demanding pre-processing techniques such as stochastic analysis employing a hidden markov model or an acoustic data filtering and hence are burdensome for real-time chord classifications. For this reason, we construct various perceptron neural networks and convolutional neural networks that use only Fourier tranform for data pre-processing and compare them with dataset obtained by playing an electric guitar. According to our comparison, convolutional neural networks provide optimal performance considering both chord classification acurracy and fast processing time. In particular, convolutional neural networks exhibit robust performance even when only small fraction of low frequency components of the data are used.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.1
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• pp.24-32
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• 2006

In this paper, we proposed the multimedia call admission control algorithm with the bandwidth reservation based on the prediction of wireless terminal's location to guarantee quality of service for multimedia applications in cellular networks. This algorithm aims at minimizing possible errors In predicting the moving direction of terminals using a mobility prediction scheme. This prediction reduces the size of bandwidth reserved redundantly. In order to evaluate the performance of the algorithm, the blocking rate of new calls and the forced termination rate of hand-off calls are measured and compared the results with those of existing schemes. The results of the experiment revealed that the algorithm presented in this paper achieved better performance with lower call blocking rates and forced-termination rates than those of other methods.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.244-248
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• 2007

In this paper, we propose a novel self-networking and replaceable structure method for the ubiquitous multimedia. As the contents in the ubiquitous multimedia should be realistic and continuously updated in the real-time manner, an efficient scheme of a self-networking and replaceable structure is necessary. In the proposed method, the contents itself connects to the server or corresponding devices and updates itself autonomously. Also, we can reduce the total amount of data transmission comparing to the cases where the whole contents should be downloaded. A Markov chain model is introduced for the proposed structure in order to perform the throughput analysis. The whole mechanism is implemented in the wireless handset and also, various applications of the scheme are discussed.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.7-11
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• 2003

Nowadays, as digital technologies are rapidly developed and requirements for the various types of broadband multimedia services increases, the radio broadcasting is moving to digitalization. DAB(Digital Audio Broadcasting), as an alternation of existing analog radio broadcasting, is a new type of multimedia broadcasting system. DAB supports not only high-quality audio broadcasting but also various types of multimedia data services. In this paper, we investigate the performance optimization method of MOT Protocol, as the standard for additional services, to support the multimedia services in the DAB network. Because the performance of the MOT protocol is dependent on various parameters such as segment size, segment repetition and so on, we find those by simulation for performance optimization. According to simulation results, the suitable segment size is about 2Kbyte and segment repetition is 4 times for performance optimization.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.2
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• pp.45-52
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• 2006

Mobile Ad-hoc Network(MANET) could be applied to various applications by virtue of its characteristics such as self-organizing and infrastructure-free network. This paper proposes a multimedia application service model for MANET, called multi-hop Relay(mRelay) system. It supports a multi-hop communication-based multimedia service interworked with Internet by using an unmanned moving robot with wireless multimedia communication function as a mRelay terminal. The modified AODV routing protocol was applied to the terminal and it was verified that composition and maintenance of mobile Ad-hoc network in mRelay system under the various indoor scenarios were successful and stable multi-hop multimedia services were possible. The mRelay system can be applicable to various application services of mobile Ad-hoc networks.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1775-1781
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• 2016

Generally, in the underwater target recognition, feature vectors are extracted from the target signal utilizing spatial information according to target shape/material characteristics. In addition, various signal processing techniques have been studied to extract feature vectors which are less sensitive to the location of the receiver. In this paper, we synthesized active echo signals using 3-dimensional highlight distribution. Then, Fractional Fourier transform was applied to echo signals to extract signal features. For the performance verification, classification experiments were performed using backpropagation and probabilistic neural network classifiers based on single aspect and multi-aspect method. As a result, we obtained a better recognition result using proposed feature extraction and multi-aspect based method.

• Journal of Multimedia Information System
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• v.2 no.3
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• pp.275-280
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• 2015

Recently brainwaves are utilized diversely in the field of medicine, entertainment, education and so on. In the case of medicine, brainwaves are analyzed to estimate patients' diseases. However, the applications for entertainments usually utilize brainwaves as control signal without figuring out the characters of the brainwaves. Given that users' brainwaves are different each other, a normalization method is essential. The traditional brainwave normalization approaches utilize normal distribution. However, those approaches assume that brainwaves are collected enough to conduct normal distribution. When the few amounts of brainwaves are measured, the accuracy of the control signal based on the measured brainwaves becomes low. In this paper, we propose a normalization framework of BCI-based facial interfaces for novel volume controllers, which can normalizes the few amounts of brainwaves and then generates the control signals of BCI-based facial interfaces. In the experiments, two subjects were involved to validate the proposed framework and then the normalization processes were introduced.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.594-596
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• 1999

It is extremely important to compress a very large multimedia data under the currently used communication networks because of the forthcoming high fast multimedia informations. Wavelets are very popular and useful mathematical tool in the field of signal processing recently. In this paper, signal compression methods using the wavelet packet transform are compared with the other compression method under same threshold condition. As the result, the compression of using the wavelet packet transform is much more effective than the other compressing methods.