• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.81-84
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• 2000

Fractal image compression can reduce the size of image data by contractive mapping of original image. The mapping is affine transformation to find the block(called range block) which is the most similar to the original image. Fractal is very efficient way to reduce the data size. However, it has high distortion rate and requires long encoding time. In this paper, we present the simulation result of fractal and VQ hybrid systems which use different clustering algorithms, normal and improved competitive learning SOFM. The simulation results showed that the VQ hybrid fractal using improved competitive learning SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• The Journal of the Acoustical Society of Korea
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• v.17 no.7
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• pp.57-60
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• 1998

본 논문에서는 MKM(Modified K-Means) 알고리듬의 성능을 개선하기 위해 새로운 학습알고리듬을 제안한다. MKM 알고리듬에서 새로운 코드워드는 이전 코드워드와 새로 얻 은 중심점을 이은 직선 상의 임의적으로 선택된다. 따라서 MKM 알고리듬은 통계적 이완 방법의 코드북 교란 알고리듬으로 이해될 수 있다. MKM 알고리듬을 통계적 이완 알고리듬 과 비교해보면 도입되는 교란의 양이 상대적으로 적고 그 교란 자체도 임의적이지 않다는 걸 알 수 있다. 따라서 MKM 알고리듬에 도입되는 교란의 양을 보다 크고 임의적이게 하면 MKM 알고리듬이 국소 최적화에 빠질 가능성이 줄어들 것이다. 따라서 본 논문에서는 MKM 알고리듬의 코드북 갱신과정을 변화시킨 새로운 알고리듬을 제안하였으며, 화상 데이 터와 음성 데이터를 이용하여 실험한 결과 제안된 알고리듬이 MKM 알고리듬보다 우수한 성능을 보인다는 걸 확인할 수 있다.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.106-109
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• 1998

Wireless communication systems, in particular, must operate in a crowded electro-magnetic environmnet where in-band undesired signals are treated as noise by the receiver. These interfering signals are often random but not Gaussian Due to nongaussian noise, the distribution of the observables cannot be specified by a finite set of parameters; instead r-dimensioal sample space (pure noise samples) is equiprobably partitioned into a finite number of disjointed regions using quantiles and a vector quantizer based on training samples. If we assume that the detected symbols are correct, then we can observe the pure noise samples during the training and transmitting mode. The algorithm proposed is based on a piecewise approximation to a regression function based on quantities and conditional partition moments which are estimated by a RMSA (Robbins-Monro Stochastic Approximation) algorithm. In this paper, we develop a diversity combiner with modified detector, called Non-Linear Detector, and the receiver has a differential phase detector in each diversity branch and at the combiner each detector output is proportional to the second power of the envelope of branches. Monte-Carlo simulations were used as means of generating the system performance.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.5
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• pp.765-776
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• 1995

This paper describes a speaker adaptation method to improve the recognition performance of MLP(multiLayer Perceptron) based HMM(Hidden Markov Model) speech recognizer. In this method, we use lst-order linear transformation network to fit data of a new speaker to the MLP. Transformation parameters are adjusted by back-propagating classification error to the transformation network while leaving the MLP classifier fixed. The recognition system is based on semicontinuous HMM's which use the MLP as a fuzzy vector quantizer. The experimental results show that rapid speaker adaptation resulting in high recognition performance can be accomplished by this method. Namely, for supervised adaptation, the error rate is signifecantly reduced from 9.2% for the baseline system to 5.6% after speaker adaptation. And for unsupervised adaptation, the error rate is reduced to 5.1%, without any information from new speakers.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.8
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• pp.77-85
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• 1998

This paper proposes progressive image transmission(PIT) methods based on the wavelet packet transform, in which quantizers are optimized at each stage for the given bit rate. Scalar and vector quantizers are used and the performance of each quantizer is compared. After quantization, selected subbands are ordered by their priority for transmission. Subjective quality of the reconsetructed image is improved by human visual system (HVS) weighting.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.1106-1111
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• 1999

Discrete cosine Transform (DCT) is most popular block transform coding in lossy mode. DCT is close to statistically optimal transform - the Karhunen Loeve transform. In this paper, a module for still image encoder is implemented with TMS320C80 based on JPEG, which are international standards for image compression. Th still image encoder consists of three parts- a transformer, a vector quantizer and an entropy encoder.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.68-80
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• 1996

In this paper, we propose a novel color image segmentation algorithm based on clustering in 3-dimensional color space employing the mathematical morphology. More specifically, since we take into account the topological properties such as the shape, connectivity and distribution of clusters in the clustering process, the number of clusters in the color cube, as well as their centers, can be easily obtained, without a priori knowledge on the input images. Intensive computer simulation has been performed and the results are discussed in this paper. The resutls of the simulation on the images in various color coordinates show that the segmentation is independent of the choice of color coordinates and the shape of clustes. Segmentation results of the vector quantizer are also presented for the comparison purpose.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.1383-1392
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• 1995

In this paper, the method to incorporate TCVQ(Trellis Copded Vector Quantizer) into the encoding of the wavelet trans formed(WT) image followed by a variable length coding(VLC) or an entropy coding(EC) is considered. By WT, an original image is separated into 10 bands with various resolutions and directional components. TCVQ used to compress these WT coefficients is a finite state machine that encodes the input source on the basis of the current input and the current state. Wavelet basis used in this paper is designed by orthogonal spline function. A modified set partitioning algorithm to Wang's is also presented. A simple modification to Wang's algorithm gives a highly time-efficient result. Proposed WT-TCVQ encoder shows a very competitive result, giving 37.46dB in PSNR at 1.002bpp when encoding 512$\times$512 LENA.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.21-30
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• 1990

This paper describes a hardware implementation of the interframe monochrome video CODEC using a MC-CVQ(Motion Compensated and Classified Vector Quantization) algorithm. The specifications of this CODEC are (1) the resolution of image is $128{\times}128$ pixels, and (2) the transmission rates are about 10frames/sec at the 64Kbps channel. In order to design the CODEC under these conditions, it is implemented by a multiprocessor system composed of MC unit, CVQ nuit and decoder unit, which are controlled by microprogramming technique. And the 3~stage pipelined ALU(Arithmetic and Logic Unit) is adopted to calculate the minimum error distance in the MC unit and CVQ nuit. The realized system shows that the transmission rates are 6-15 frames/sec according to the relative motion of the video signal.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.10
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• pp.118-125
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• 1998

We introduce an adaptive finite state vector quantization using a new side match distortion function. The conventional side match distortion function can make the gray level transition between the block bounddaries as smooth as possible and proper state codebooks in the flat areas where the spatial correlations are high. But it can't make proper codebooks in the edge areas where the spatial correlations are not high. The proposed distortion function adds the variances which represent the image characteristics to the conventional side match distortion function as weighted values. Then it can select better state codebooks than the conventional side match distortion function. Also if it predicts a wrong state, the proposed quantizer can correct the state. As a result, we can obtain the satisfiable image quality.