• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.159-163
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• 1996

In this paper, a new image compression technique, which uses lifting scheme and pyramid vector quantization, is proposed. Lifting scheme is a new technique to generate wavelets and to perform wavelet transform, and pyramid vector quantization is a kind of vector quantization which dose not have codebook neither codebook generation algorithm. For the purpose of realizing more compression rate, an arithmetic entropy coder is used. Proposed algorithm is compared with other wavelet based image coder and with JPEG which uses DCT and adaptive Huffman entropy coder. Simulation results showed that the performance of proposed algorithm is much better than that of others in point of PSNR and bpp.

• Journal of KSNVE
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• v.10 no.2
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• pp.331-337
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• 2000

The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Many research has been conducted to manipulate field vibration signal data for diagnosing the fault of designated machinery. As the pattern recognition tool of that signal, neural network which use usually back-propagation algorithm was used in the diagnosis of rotating machinery. In this paper, self-organizing feature map(SOFM) which is unsupervised learning algorithm is used in the abnormal defect diagnosis of rotating machinery and then learning vector quantization(LVQ) which is supervised learning algorithm is used to improve the quality of the classifier decision regions.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.197-200
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• 1998

본 논문에서는 유전자 알고리즘(genetic Algorithm)을 사용하여 벡터 양자화(vector quantization : VQ)를 수행하는 방법을 제안하고자 한다. 벡터 양자화를 수행하여 코드북(codebook)을 생성할 때 생성된 코드북과 학습벡터(training vector)사이에는 반드시 양자화 오차(quantization error)가 발생하는데 기존의 K-means 알고리듬을 사용하여 코드북을 생성했을 경우 양자화 오차를 줄이는데 한계가 있었다. 본 논문에서 제안하는 유전자 알고리즘을 이용한 벡터 양자화는 이 양자화 오차를 감소시키기 위해서 연구되었다. 제안한 방법의 성능을 평가하기 위해 음성데이터를 기존의 K-means 알고리즘에서 클러스터의 중심을 선택하는 방법중의 하나인 Minimax방법으로 코드북을 생성하여 제안한 방법과 양자화 오차를 비교한 결과 양자화 오차가 감소됨을 알 수 있었다.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4E
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• pp.31-38
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• 2001

A large-scale synthesis database for a unit selection based synthesis method usually retains redundant synthesis unit instances, which are useless to the synthetic speech quality. In this paper, to eliminate those instances from the synthesis database, we proposed a new pruning method called weighted vector quantization (WVQ). The WVQ reflects relative importance of each synthesis unit instance when clustering the similar instances using vector quantization (VQ) technique. The proposed method was compared with two conventional pruning methods through the objective and subjective evaluations of the synthetic speech quality: one to simply limit maximum number of instance, and the other based on normal VQ-based clustering. The proposed method showed the best performance under 50% reduction rates. Over 50% of reduction rates, the synthetic speech quality is not seriously but perceptibly degraded. Using the proposed method, the synthesis database can be efficiently reduced without serious degradation of the synthetic speech quality.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.470-473
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• 2004

In this paper, the comparison of speech feature parameters for emotion recognition is studied for emotion recognition using speech signal. For this purpose, a corpus of emotional speech data recorded and classified according to the emotion using the subjective evaluation were used to make statical feature vectors such as average, standard deviation and maximum value of pitch and energy. MFCC parameters and their derivatives with or without cepstral mean subfraction are also used to evaluate the performance of the conventional pattern matching algorithms. Pitch and energy Parameters were used as a Prosodic information and MFCC Parameters were used as phonetic information. In this paper, In the Experiments, the vector quantization based emotion recognition system is used for speaker and context independent emotion recognition. Experimental results showed that vector quantization based emotion recognizer using MFCC parameters showed better performance than that using the Pitch and energy parameters. The vector quantization based emotion recognizer achieved recognition rates of 73.3％ for the speaker and context independent classification.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.87-90
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• 2008

디지털 워터마킹은 디지털 콘텐츠에 워터마크를 삽입함으로써 불법적인 복제를 방지하고, 지적재산권 및 저작권을 보호하며, 소유권을 주장할 수 있는 근거를 제시하는 기술이다. 기존의 워터마킹 기법에서는 워터마크를 삽입함으로써 데이터 왜곡과 품질 저하가 불가피하다는 단점이 있다. 이를 극복하기 위하여 원래 데이터를 변경하지 않는 제로-워터마킹 기법들이 제시되고 있다. 이 논문에서는 VQ(Vector Quantization) 방식의 블록 효과를 줄이고, 압축 비율과 품질을 향상시킨 SMVQ(Side Match Vector quantization) 방식에 대한 제로-워터마킹 체계인 CSMVQ(Chaotic SMVQ)를 제안한다. SMVQ 이미지 압축에서는 동일하게 두 이웃 블록의 접면 정보를 이용하기 위하여 좌측 상단에서 우측 하단으로 진행되므로, 임의의 순서로 블록을 선택하여 워터마크를 삽입하기 어렵다. CSMVQ에서는 이전에 부호화된 이웃 블록들의 접면 정보의 일치성을 동적으로 고려하여 부호화를 진행한다. 그러므로 무질서한 방식으로 워터마크가 삽입되도록 지원할 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2372-2382
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• 1998

In this paper, we propose a new edge based finite state vector quantization method having better performance than conventional side-match finite state vector quantization. In our proposed scheme, each dCT transformed block is classified to 17 classes according to edge types. Each class has a different codebook based on its characteristis. Encoder classified each block to motion block or stationary block and constructed a merging map by using edge and motion information, and sent to decoder. We controled amoutn of bing bits transmitted with selecting modes accoridng to bandwidth of transmitting channel. Compared with conventional algorithms, H.263 and H.261 at low bit rate, our proposed algorithm shows better picture quality and good performance.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.131-137
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• 1997

In this paper, we propose an efficient motion adaptive 3-dimensional (3D) video coding algorithm using 3D subband coding (3D-SBC) and lattice vector quantization (LVQ) for low bit rate. Instead of splitting input video sequences into the fixed number of subbands along the temporal axes, we decompose them into temporal subbands of variable size according to motions in frames. Each spatio-temporally splitted 7 subbands are partitioned by quadtree technique and coded with lattice vector quantization(LVQ). The simulation results show 0.1∼4.3dB gain over H.261 in peak signal to noise ratio (PSNR) at low bit rate(64Kbps).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.9
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• pp.927-938
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• 1992

In 1-D subband coding system, a quadrature mirror filter (QMF) pair can be used to split a signal into two subbands and to reconstruct the original signal. In this paper, a pair of 1-D reconstruction filter for the subband coding system is introduced and a coding technique with classified vector quantization, based on energy distributions, for 16 subband images is presented. As computer simulation results show that the method can give similar perceptual quality with bit rate reduced by $20{\sim}30%$ of that of ordinary vector quantization.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.374-381
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• 1991

As a diagnostic image of hospitl, the utilization of digital image is steadily increasing. Image coding is indispensable for storing and compressing an enormous amount of diagnostic images economically and effectively. In this paper adaptive two stage vector quantization based on Kohonen's neural network for the compression of cardioangiography among typical angiography of radiographic image sequences is presented and the performance of the coding scheme is compare and gone over. In an attempt to exploit the known characteristics of changes in cardioangiography, relatively large blocks of image are quantized in the first stage and in the next stage the bloks subdivided by the threshold of quantization error are vector quantized employing the neural network of frequency sensitive competitive learning. The scheme is employed because the change produced in cardioangiography is due to such two types of motion as a heart itself and body motion, and a contrast dye material injected. Computer simulation shows that the good reproduction of images can be obtained at a bit rate of 0.78 bits/pixel.