• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2447-2449
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• 2003

In this paper, optimal fuzzy systems using vector quantization and fuzzy logic controllers are designed for vision-based robot control systems. The complexity of the optimal fuzzy system for vision-based control systems is so great that it can not be applied to real vision-based control systems or it can not be useful, because there are so many input-output pairs. Therefore, we generally use the clustering of input-output pairs, in order to reduce the complexity of optimal fuzzy systems. To increase the effectiveness of the clustering, a vector quantization clustering method is proposed. In order to verify the effectiveness of the proposed method experimentally, it is applied to a vision-based arm robot control system.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.225-228
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• 1996

ECG data are used for the diagnostic purposes with many clinical situations, especially heart disease. In this paper, an efficient ECG data compression technique by wavelet transform and high-speed vector quantization on PMS-B algorithm is proposed. In general, ECG data compression techniques are divided into two categories: direct and transform methods. The direct data compression techniques are AZTEC, TP, CORTES, FAN and SAPA algorithms, besides the transform methods include K-L, Fourier, Walsh, and wavelet transforms. In this paper, we applied wavelet analysis to the ECG data. In particular, vector quantization on PMS-B algorithm to the wavelet coefficients in the higher frequency regions, but scalar quantized in the lower frequency regions by PCM. Finally, the quantized indices were compressed by LZW lossless entropy encoder. As the result of simulation, it turns out to get sufficient compression ratio while keeping clinically acceptable PRD.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.04a
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• pp.1051-1055
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• 2000

본 연구에서는 내용기반 영상 데이터 검색을 위하여 변환 영역에서 위치 정보와 주파수 정보를 가지는 웨이블릿 성질을 이용하여 객체들의 특징을 추출하는 방안인 Vector Quantization 을 이용한 영상을 검색하는 방안을 제시한다. 내용기반 영상 검색의 주요 특징들은 색상, 질감, 그리고 영상의 공간적인 특징을 고려한 특징 값 등이 사용된다. 이러한 영상의 특징들을 어떻게 결합하고 특징 추출을 하느냐에 따라 검색의 효율성에 영향을 준다. 따라서 본 연구에서는 영상의 위치 정보와 주파수 정보를 가지는 웨이블릿 변환 후 얻어지는 저대역 부밴드에서의 공간적인 특성을 고려한 특징 값을 이용하여 Vector Quantization 알고리즘에 의해 정지영상의 객체 대표 특징들을 빠르게 검색하고자 한다. 본 연구에서는 Haar Wavelet 과 Vector Quantization 에서 색상과 질감의 가중치를 적용하고자 한다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.4
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• pp.50-56
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• 1997

In this paper, efficient quantization methods of line spectrum pairs (LSP) which has good performances and low complexity and memory are proosed for vocoder of mobile communication system. The adaptive quantization method utilizing the ordering property of LSP parameters is used in a scalar quantizer and a vector-scalar hybrid quantizer. The proposed scalar quantization algorithm needs 31 bits/frame to maintain the transparent quality of speech. The improved vector-scalar quantizer achieves an average spectral distortion of 1dB using 26 bits/frame. The proposed methods are evaluated in the channel errors and changed the predictor structure to maintain the robustness to channel errors.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.142-147
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• 2018

We present a practical design algorithm for quantizers at nodes in distributed systems in which each local measurement is quantized without communication between nodes and transmitted to a fusion node that conducts estimation of the parameter of interest. The benefits of vector quantization (VQ) motivate us to incorporate the VQ strategy into our design and we propose a low-complexity design technique that seeks to assign vector codewords into sets such that each codeword in the sets should be closest to its associated local codeword. In doing so, we introduce new distance metrics to measure the distance between vector codewords and local ones and construct the sets of vector codewords at each node to minimize the average distance, resulting in an efficient and independent encoding of the vector codewords. Through extensive experiments, we show that the proposed algorithm can maintain comparable performance with a substantially reduced design complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.10
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• pp.2634-2644
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• 1996

Two different low rate speech coders using one of four types of lattice vector quantizers(LVQ's) with fairly low complexity were investigated for an application to mobile communications. More specifically, two-stage vector quantizer-lattic vector quantizer(VQ-LVQ) systems and vector differenctial pulse code modulation(VDPCM)systems with lattice vector quantizers simulated to encode the line spectrum frequencies of various sentences at the rate 22 to 39 bits per 20 msec frame. The simulation results showed that the VDPCM system with the lattice VQ can save up to 10 bits/fram compared to the quantization scheme used in QCELP system. For the VQ-LVQ system, the spherical quasi-uniform LVQ below 36 bits/frame outperformed the other 3 types of LVQ's and the pyramidal quasi-uniform LVQ at 37 bits/frame outperformed the other 3 types of LVQ's with the spectral distortion 0.97.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.243-252
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• 2024

Among the Foley sound generation models that have recently begun to be studied, a sound generation technique using the Vector Quantized-Variational AutoEncoder (VQ-VAE) structure and generation model such as Pixelsnail are one of the important research subjects. On the other hand, in the field of deep learning-based acoustic signal compression, residual vector quantization technology is reported to be more suitable than the conventional VQ-VAE structure. Therefore, in this paper, we aim to study whether residual vector quantization technology can be effectively applied to the Foley sound generation. In order to tackle the problem, this paper applies the residual vector quantization technique to the conventional VQ-VAE-based Foley sound generation model, and in particular, derives a model that is compatible with the existing models such as Pixelsnail and does not increase computational resource consumption. In order to evaluate the model, an experiment was conducted using DCASE2023 Task7 data. The results show that the proposed model enhances about 0.3 of the Fréchet audio distance. Unfortunately, the performance enhancement was limited, which is believed to be due to the decrease in the resolution of time-frequency domains in order to do not increase consumption of the computational resources.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.21-26
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• 2004

Color image quantization is a process of selecting a set of colors to display an image with some representative colors without noticeable perceived difference. It is very important in many applications to display a true color image in a low cost color monitor or printer. The basic problem is how to display 256 colors or less colors, called color palette, In this paper, we propose improved binary tree vector quantization based on spatial sensitivity which is one of the human visual properties. We combine the weights based on the responsibility of human visual system according to changes of three Primary colors in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get the better result in subjective quality test and WSNR.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.18-27
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• 2012

Optimal quantizers in conducting the entropy-constrained quantization for high bit rates have the lattice structure. The quantization process is simple due to the regular structure and various quantization algorithms are proposed depending on the lattice. In this paper, such a lattice vector quantization is implemented by using the sample-adaptive product quantizer (SAPQ). It is shown that several important lattices can be implemented by SAPQ and the lattice vector quantization can be performed by using a simple integer-transform function of scalar values within SAPQ. The performance of the proposed lattice SAPQ is compared to the entropy-constrained scalar quantizer and the entropy-constrained SAPQ (ECSAPQ) at a similar encoding complexity. Even though ECSAPQ shows a good performance at low bit-rates, lattice SAPQ shows better performance than the ECSAPQ case for a wide range of bit rates.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.5
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• pp.767-774
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• 1990

Successive images can be reconstructed without great degradation by using one codebook in vector quantization, because statistics of successive images are sinilar. In this paper, we propose a method to update vector centroids in one slot of an image sequence and reconstruct images with the codebook replenished with the updated vector centroids. To remove the overhead required to transmit the updated vector centroids, we catagorize image blocks into changing blocks and nonchanging blocks, and then transmit only the labels of the changing blocks. Therefore, we can assign the remaining bits to the replenishment of a codebook. By the proposed method, almost the same image as the same image as the one reconstructed by LBG algorithm can be obtained and the bit rate can be reduced to below 0.5 bit/pixel.