• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.91-96
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• 2010

Concentric mosaics are made with arranging and summing of video frames by using common spacial standards. Compared with previous works on 3-D wavelet transform coding, we have made important design considerations to enable flexible partial decoding and bit-stream random access. A just-in-time(JIT) rendering engine of the compressed concentric mosaic is developed. However, computationally, it is still demanding to accomplish the real-time rendering. Only the contents for specific scene representation are need to be decoded by maintaining compressed data. Thus our proposed algorithm is able to render real concentric mosaic by using lifting scheme instead of wavelet transform.

• Korean Journal of Cognitive Science
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• v.14 no.4
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• pp.33-42
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• 2003

This paper presents a new system for facial expression recognition based in dimension model of internal states. The information of facial expression are extracted to the three steps. In the first step, Gabor wavelet representation extracts the edges of face components. In the second step, sparse features of facial expressions are extracted using fuzzy C-means(FCM) clustering algorithm on neutral faces, and in the third step, are extracted using the Dynamic Model(DM) on the expression images. Finally, we show the recognition of facial expression based on the dimension model of internal states using a multi-layer perceptron. The two dimensional structure of emotion shows that it is possible to recognize not only facial expressions related to basic emotions but also expressions of various emotion.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.751-753
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• 1999

본 논문에서는 영상의 텍스쳐 정보를 이용하여 일반 영상에 대한 내용기반 영상 검색을 수행할 수 있는 알고리듬을 제안한다. Gabor 웨이브렛 변환을 이용하여 Gabor 필터 뱅크 내의 각 필터에 의해 필터링된 대역의 평균과 표준편차를 영상의 특징 벡터(Gabor Texture Feature)로 추출하여 영상들간의 유사성을 계산하는데 사용한다. 논문의 목적이 영상에 가해진 외적 변형, 즉 잡음 첨가, 블러링, 샤프닝 등과 같은 변형에 강인하게 동작할 수 있는 텍스쳐 특징 기반 영상 검색 기법을 제안하는 것이므로, 기존의 Gabor 필터만을 사용하여 텍스쳐 특징을 추출하여 검색의 기준으로 삼을 경우에 발생할 수 있는 주파수 성분의 변화에 대한 민감성을 Daubechies의 웨이브렛 필터를 사용하여 낮은 해상도에서 영상을 해석함으로써, 외적 변형에 대하여도 강인하게 동작할 수 있는 알고리듬을 제시하였다. 기존의 텍스쳐를 이용한 검색이 주로 텍스쳐 영역(textured region)에 대한 해석만을 하였지만, 본 논문에서는 이를 일반 영상에 적용하였으며, 일반 영상에 대해서도 효율적인 검색을 수행할 수 있음을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.948-955
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• 2006

In this paper, we propose motion estimation and compensation using Low-Band-Shift(LBS) with Integer Lifting Shift property. To overcome shift-variant property on wavelet coefficients, the LBS was previously proposed. This method which is applied to reference frame in video coding technique has superior performance in terms of rate-distortion characteristic. However, this method needs more memory and computational complexity. For the enhancement of those disadvantages, we propose motion estimation using Low-Band-Shift with Integer Lifting. The Integer Lifting implementation gives us good efficiency of calculation and storage.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.6
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• pp.24-35
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• 2002

The wavelet transform is combined with the boundary element method (BEM), to solve efficiently the Maxwell's equation and the proposed method is applied to the electromagnetic problem for the analysis of topological effects of phase-shifting masks. The accuracy of the module developed was verified by comparison with both analytic solutions and published results. In addition, it was found that the boundary element method in combination with the wavelet matrix transform would be more efficient than the conventional methods based on the BEM in views of the calculation speed and the usage of computer memory.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.796-801
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• 2000

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a signal classification method for diagnosing the rotating machinery using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them are compared with each other. This paper is focused on the development of an advanced signal classifier to automatise the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.37-43
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• 2023

Compressed still image or video bitstreams require protection from channel errors in a wireless channel. Embedded Zerotree Coding(EZW), SPIHT could have provided unprecedented high performance in image compression with low complexity. If bit error is generated by dint of wireless channel transmission problem, the loss of synchronization on between encoder and decoder causes serious performance degradation. But wavelet zerotree coding algorithms are producing variable-length codewords, extremely sensitive to bit errors. The idea is to partition the lifting coefficients. A many partition of lifting transform coefficients distributes channel error from wireless channel to each partition. Therefore synchronization problem that caused quality deterioration in still image and video stream was improved.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.8
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• pp.101-112
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• 1999

In this paper, the codebook design method of VQ (vector quantization) is proposed an method to extract feature data of image for multimedia information searching. Conventional VQ codebook design methods are unsuitable to extract the feature data of images because they have too much computation time, memory for vector decoding and blocking effects like DCT (discrete cosine transform). The proposed design method is consists of the feature extraction by WT (wavelet transform) and the data group divide method by PCA (principal component analysis). WT is introduced to remove the blocking effect of an image with high compressing ratio. Computer simulations show that the proposed method has the better performance in processing speed than the VQ design method using SOM (self-organizing map).

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.46-53
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• 1996

Adaptive LMS algorithm has been used in many application areas due to its low complexity. In this paper input signal is transformed into the subbands with arbitrary bandwidth. In each subbands the dynamic range can be reduced, so that the independent filtering in each subbands has faster convergence rate than the full band system. The DCT transform domain LMS adaptive filtering has the whitening effect of input signal at each bands. This leads the convergence rate to very high speed owing to the decrease of eigen value spread Finally, the filtered signals in each subbands are synthesized for the output signal to have full frequency components. In this procedure wavelet filter bank guarantees the perfect reconstruction of signal without any interspectra interference. In simulation for the case of speech signal added additive white gaussian noise, the suggested algorithm shows better performance than that of conventional NLMS algorithm at high SNR.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.216-222
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• 2008

This paper proposed the multi characters detection algorithm using Color segmentation and the closing curve feature of LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of left and background color, etc. The proposed multi characters detection algorithm divided into three parts : The feature detection, characters format and characters detection Parts in order to be possible to apply to image of various feature. After preprocess that the new multi characters detection algorithm that proposed in this paper used wavelet, morphology, hough transform which is the synthesis logical model in order to raise detection rate by acquiring the non-perfection characters as well as the perfection characters with processing OR operation after processing each color area by AND operation sequentially. And the proposal algorithm is simulated with natural images which include natural character area regardless of size, resolution and slant and so on of image. And the proposal algorithm in this paper is confirmed to an excellent detection rate by compared with the conventional detection algorithm in same image.