• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.4
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• pp.772-780
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• 1994

Vector quantization with two-channel conjugate codebook has been researched as an efficient coding technique that can reduce the computational complexity and codebook storage. This paper proposes FSVQ using two-channel conjugate codebook in order to reduce the number of state codebooks. Input vector in the two-channel conjugate FSVQ is coded with state codebook of a seperated state according to each codebook. In addition, LOT is adopted to obtain to obtain a high coding gain and to reduce blocking effect which appears in the block coding. As a result, although FSVQ can achieve higher data compression ratio than general vector quantization, it has a disadvantage of having a very large number of state codebooks. However FSVQ with two-channel conjugate codebooks can employ a significantly reduced number of state codebooks, even though it has a small loss in the PSNR compared with the conventional FSVQ using one codebook. Moreover FSVQ in the LOT domain can reduce blocking effect and high coding gain compared with FSVQ in the spatial domain.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.127-136
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• 1998

This paper proposes a new MVQMultistage Vector Quantizer) using a hybrid structure. While in a conventional MVQ, the quantizers of all stages perform the encoding procedure for input signals, we introduce a quantizer that performs selectively. The proposed quantizer with a hybrid structure is composed of a FSVQ(Finite-State Vector Quantizer) for the first stage and a ordinary VQ(Vector Quantizer) for the second stage. A input block is firstly encoded by the FSVQ of the first stage. If the Euclidean distortion measure between original signals and the codevector selected from the state codebook of the FSVQ is less than a prespecified value, only the FSVQ is used for image coding. Otherwise, both the FSVQ of the first stage and the ordinary VQ of the second stage are used for image coding. While the conventional MVQ has an advantage that can achieve low encoding complexity in comparison to the ordinary VQ, but has a disadvantage that is suboptimal with respect to the performance measure and can not achieve the bit rate reduction, the proposed method achieve not only the bit rate reduction but also the performance improvement.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.90-97
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• 2003

This paper proposes a speech recognition based on HMM(Hidden Markov Model) using FSVQ(First Section Vector Quantization) and fuzzy concept. In the proposed paper, we generate codebook of First Section, and then obtain multi-observation sequences by order of large propabilistic values based on fuzzy rule from the codebook of the first section. Thereafter, this observation sequences of first section from codebooks is trained and in case of recognition, a word that has the most highest probability of first section is selected as a recognized word by same concept. Train station names are selected as the target recognition vocabulary and LPC cepstrum coefficients are used as the feature parameters. Besides the speech recognition experiments of proposed method, we experiment the other methods under same conditions and data. Through the experiment results, it is proved that the proposed method based on HMM using FSVQ and fuzzy concept is superior to tile others in recognition rate.

• Journal of the Korea Computer Industry Society
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• v.5 no.4
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• pp.491-502
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• 2004

In this paper, we propose a HMM model using FSVQ(First Section VQ), fuzzy theory and doubly spectral feature, as study on the isolated word recognition system of speaker-independent. In the proposed paper, LPC cepstrum coefficients and regression coefficients of LPC cepstrum as doubly spectral feature be used. And, training data are divided several section and first section is generated codebook of VQ, and then is obtained multi-observation sequences by order of large propabilistic values based on fuzzy nile from the codebook of the first section. Thereafter, this observation sequences of first section is trained and is recognized a word to be obtained highest probaility by same concept. Besides the speech recognition experiments of proposed method, we experiment the other methods under the equivalent environment of data and conditions. In the whole experiment, it is proved that the proposed method is superior to the others in recognition rate.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.1013-1020
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• 2000

In this paper, we propose an algorithm which segments hierarchically blocks of image using discrete cosine transform(DCT) and execute finite-state vector quantization (FSVQ) for each block. Using DCT coefficient feature, image is segmented hierarchically to large smooth block and small edge block, then the block hierarchy informations are transmitted. The codebooks are respectively constructed for each hierarchical blocks, the encoder transmits codeword index using FSVQ for reducing encoded bit with hierarchical segmentation. Compared with side match VQ(SMVQ) and hierarchical FSVQ(HFSVQ) algorithm, about Zelda and Boat image, the new algorithm shows better picture quality with 1.97dB and 2.85 dB difference as to SMVQ, 1.78dB and 1.85dB diffences as to HFSVQ respectively.

• Journal of Internet Computing and Services
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• v.6 no.2
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• pp.59-68
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• 2005

In this paper, for compression and transmission of 3D image, we propose an algorithm which executes 3D discrete cosine transform(DCT) for 3D images, hierarchically segments 3D blocks of an image in comparison with the original image and executes finite-state vector quantization(FSVQ) for each 3D block. Using 3D DCT coefficient feature, a 3D image is segmented hierarchically into large smooth blocks and small edge blocks, then the block hierarchy informations are transmitted. The codebooks are constructed for each hierarchical blocks respectively, the encoder transmits codeword index using FSVQ for reducing encoded bit with hierarchical segmentation information. The new algorithm suggested in this paper shows that the quality of Small Lobster and Head image increased by 1,91 dB and 1.47 dB respectively compared with those of HFSVQ.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2615-2628
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• 1997

In this paper, a new codebook design algorithm is proposed. It uses a DCT map based on two-dimensional discrete cosine of transform (2D DCT) and finite state vector quantizer (FSVQ) when the vector quantizer is designed for image transmission. We make the map by dividing input image according to edge quantity, then by the map, the significant features of training image are extracted by using the 2D DCT. A master codebook of FSVQ is generated by partitioning the training set using binary tree based on tree-structure. The state codebook is constructed from the master codebook, and then the index of input image is searched at not master codebook but state codebook. And, because the coding of index is important part for high speed digital transmission, it converts fixed length codes to variable length codes in terms of entropy coding rule. The huffman coding assigns transmission codes to codes of codebook. This paper proposes single-side growing huffman tree to speed up huffman code generation process of huffman tree. Compared with the pairwise nearest neighbor (PNN) and classified VQ (CVQ) algorithm, about Einstein and Bridge image, the new algorithm shows better picture quality with 2.04 dB and 2.48 dB differences as to PNN, 1.75 dB and 0.99 dB differences as to CVQ respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.87-94
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• 2007

In this paper, the performance of the speech recognition and speaker adaptation methods are studied. The speech recognition using energy state and VQ(Vector Quantization) is suggested and the speaker adaptation methods(Maximum a posteriori probability estimation, linear specrum estimation) are considered. The experimental results show that recognition ration using energy state is 2-3 % better than that of general VQ.

• 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.