• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2478-2484
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• 2010

In this paper, real-time detection methods for Panorama system Key-Points offers. A recent study in PANORAMA system real-time area navigation or DVR to apply such research has recently been actively. The detection of the Key-Point is the most important elements that make up a Panorama system. Not affected by contrast, scale, Orientation must be detected Key-Point. Existing research methods are difficult to use in real-time Because it takes a lot of computation time. Therefore, this paper propose BLOG(BitRate Laplacian Of Gaussian)method for faster time Key-Point Detecting and Through various experiments to detect the Speed, Computation, detection performance is compared against.

• Journal of Korea Multimedia Society
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• v.6 no.6
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• pp.1008-1014
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• 2003

In this paper, we propose the image retrieval method based on object regions using bidirectional round filter in the wavelet transform domain. A conventional method that includes unnecessary background information reduce retrieval efficiency, because of the extraction of feature vectors from the whole region of subband. On proposed method, it extracts accurate feature vectors and keep certainly retrieval efficiency in case of reduced feature vectors, because of the extraction of feature vectors from the only extracted object region. Furthermore, it improve retrieval efficiency by removing unnecessary background information. Consequently, the retrieval efficiency is improved with 2.5%∼5.5% values, which have a little chances to vary according to characteristics of image.

• The KIPS Transactions:PartB
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• v.18B no.4
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• pp.173-180
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• 2011

This paper shows an approach for real-time object segmentation on GPU (Graphics Processing Unit) using CUDA (Compute Unified Device Architecture). Recently, many applications that is monitoring system, motion analysis, object tracking or etc require real-time processing. It is not suitable for object segmentation to procedure real-time in CPU. NVIDIA provide CUDA platform for Parallel Processing for General Computation to upgrade limit of Hardware Graphic. In this paper, we use adaptive Gaussian Mixture Background Modeling in the step of object extraction and CCL(Connected Component Labeling) for classification. The speed of GPU and CPU is compared and evaluated with implementation in Core2 Quad processor with 2.4GHz.The GPU version achieved a speedup of 3x-4x over the CPU version.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.121-128
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• 2017

In this paper, we propose a dual-channel acoustic event detection (AED) method using nonnegative tensor factorization (NTF) and hidden Markov model (HMM) in order to improve detection accuracy of AED in multisource environments. The proposed method first detects multiple acoustic events by utilizing channel gains obtained from the NTF technique applied to dual-channel input signals. After that, an HMM-based likelihood ratio test is carried out to verify the detected events by using channel gains. The detection accuracy of the proposed method is measured by F-measures under 9 different multisource conditions. Then, it is also compared with those of conventional AED methods such as Gaussian mixture model and nonnegative matrix factorization. It is shown from the experiments that the proposed method outperforms the convectional methods under all the multisource conditions.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.81-97
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• 2003

In this paper, we suggest a method of robust watermarking for protection of multimedia data using the wavelet transform and artificial neural network. for the purpose of implementation, we decompose a original image using wavelet transform at level 3. After we classify transformed coefficients of other subbands using neural network except fur the lowest subband LL$_3$, we apply a calculated threshold about chosen cluster as the biggest. We used binary logo watermarks to make sure that it is true or not on behalf of the Gaussian Random Vector. Besides, we tested a method of dual watermark insertion and extraction. For the purpose of implementation, we decompose a original image using wavelet transform at level 3. After we classify transformed coefficients of other subbands using neural network except for the lowest subband LL$_3$, we apply a above mentioned watermark insert method. In the experimental results, we found that it has a good quality and robust about many attacks.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.75-83
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• 1999

This paper proposes a new F0 contour model for intonation control in speech synthesis. We assume that the F0 contour of an utterance can be described using a sequence of time-overlapping events, which determine the fluctuation of a given F0 contour, described by asymmetric Gaussian functions. In addition, We propose a parameter estimation algorithm for the proposed model. The proposed model is not developed with a particular phonological theory in mind, and can be used in both F0 contour analysis and synthesis. For testing our F0 model, we collected 500 sentences from various genres and built a corresponding speech corpus uttered by a professional female announcer. As n result of F0 resynthesis experiment using the proposed model, the RMSE was 7.87Hz for given speech corpus.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.2
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• pp.32-38
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• 2012

In this paper, we design on nonliner 3 user Dirty Paper Precoding for MIMO adjacant interference signal cancellation based on 3 GPP LTE Release 10. In this paper, in order to reduce the inter-channel interference at the transmitted side, we propose the Dirty Paper Precoding scheme for 3-user MIMO wireless systems using LQ decomposition and Gram-Schmidt algorithm based in its orthonormal basis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9C
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• pp.1298-1305
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• 2004

Most watermarking techniques embed watermarks in the middle frequency range for robustness and invisibility. In our proposed watermarking algorithms embed the gaussian sequence watermark into low frequency area of the wavelet transform domain because the histogram of low sub-band area is composed by similar coefficients. Also, our proposed scheme doesn't need the original image in extraction procedure The experimental results show good robustness against the Check Mark benchmarking tools.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.2
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• pp.67-70
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• 2016

This paper discusses a graphic user interface(GUI) for the concealed target segmentation. The human subject hiding a metal gun is captured by the passive millimeter wave(MMW) imaging system. The imaging system operates on the regime of 8 mm wavelength. The MMW image is analyzed by the multi-level segmentation to segment and identify a concealed weapon under clothing. The histogram of the passive MMW image is modeled with the Gaussian mixture distribution. LBG vector quantization(VQ) and expectation and maximization(EM) algorithms are sequentially applied to segment the body and the object area. In the experiment, the GUI is implemented by the MFC(Microsoft Foundation Class) and the OpenCV(Computer Vision) libraries and tested in real-time showing the efficiency of the system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.55-58
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• 2016

본 논문은 사람의 얼굴 영상에서 잡티를 제거하는 방법을 제안한다. 먼저 입력받은 영상에서 Haar-like Feature 기반 Adaboost 알고리즘과 색상 정보를 이용하여 얼굴 영역을 검출한다. 검출된 얼굴 영역에서 잡티를 제거하기 위해서는 먼저 눈, 코, 입, 눈썹과 같은 얼굴의 주요부위를 검출하고 이 영역을 제외한 순수 피부 영역에 잡티 검출 알고리즘을 적용해야한다. 사람의 얼굴은 미세하게 명암도 차이가 나는 부분이 많기 때문에 가우시안 스무딩을 적용한 후, 그래프 기반 분할 방법을 사용하여 눈, 입, 눈썹을 분할한다. 코 영역은 각 픽셀에 대해 인접픽셀과의 R 채널의 차이값을 가중치 맵으로 만들고 가중치 맵을 분석하여 영역을 분할한다. 분할된 영역에 사람 얼굴의 기하학적 위치 정보를 이용하여 주요부위를 검출한다. 얼굴의 주요부위를 검출하고 그 부위를 제외한 피부 영역에 잡티 검출 알고리즘을 적용한다. 잡티는 Edge와 색상 정보를 이용하여 검출하고, 잡티주변을 검사하여 잡티가 아닌 깨끗한 피부를 잡티 영역에 복사하여 채워나가는 방식으로 피부 영역을 복원한다.