• Journal of Digital Contents Society
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• v.15 no.3
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• pp.365-371
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• 2014

In the era of big data, algorithms for the existing IT environment cannot accept on a distributed architecture such as hadoop. Thus, new distributed algorithms which apply a distributed framework such as MapReduce are needed. Lloyd's algorithm commonly used for vector quantization is developed using MapReduce recently. In this paper, we proposed a decombined distributed VQ codebook generation algorithm based on a distributed VQ codebook generation algorithm using MapReduce to get a result more fast. The result of applying the proposed algorithm to big data showed higher performance than the conventional method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.10
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• pp.1-6
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• 2011

In this paper, the sum-rate and BER performances of MU-MIMO system employing quantized differential feedback technique are analyzed over temporrally correlated channels. Several differential codebooks are assumed in the analysis such as quasi-diagonal codebook, spherical cap codebook, and differential equal gain codebook. The simulation results indicates that the system employing quantized differential feedback technique provides significant performance improvement. The performance improved 0.6bps/Hz at least in terms of sum-rate, and 4dB power gain is provided in terms of average BER.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.4
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• pp.434-440
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• 2003

Since Jacquine introduced the image coding algorithm using fractal theory, many fractal image compression algorithms providing good quality at low bit rate have been proposed by Fisher and Beaumount et al.. But a problem of the previous implementations is that the decoding rests on an iterative procedure whose complexity is image-dependent. This paper proposes an iterative-free fractal image decoding algorithm to reduce the decoding time. In the proposed method, under the encoder previously with the same codebook image as an initial image to be used at the decoder, the fractal coefficients are obtained through calculating the similarity between the codebook image and an input image to be encoded. As the decoding process can be completed with received fractal coefficients and predefined initial image without repeated iterations, the decoding time could be remarkably reduced.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.11
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• pp.44-47
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• 1991

There exists a transform trellis code that is optimal for stationary Gaussian sources and the squared-error distortion measure at all rates. In this paper, we train an asymptotically optimal version of such a code to obtain one which is matched better to the statistics of real world data. The training algorithm uses the M-algorithm to search the trellis codebook and the LBG-algorithm to update the trellis codebook. To adapt the codebook for the varying input data. we use two gain-adaptive methods. The gain-adaptive scheme 1, which normalizes input block data by its gain factor, is applied to images at rate 0.5 bits/pixel. When each block is encoded at the same rate, the nonstationarity among the block variances leads to a variation in the resulting distortion from one block to another. To alleviate the non-uniformity among the encoded image, we design four clusters from the block power, in which each cluster has its own trellis codebook and different rates. The rate of each cluster is assigned through requiring a constant distortion per-letter. This gain-adaptive scheme 2 produces good visual and measurable quality at low rates.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.12
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• pp.83-89
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• 2008

Simple but effective fast codebook searching algorithms for quantized EGT(equal gain transmission) are presented. Using newly defined metric, rough searching selects a few candidate weight vectors. Using the conventional metric, accurate searching determines the optimal vector among the candidates. This strategy reduces the entire searching time. When the number of transmit antenna is two or three, the searching time reduces more than a half less than the conventional searching time. Moreover, the more the size of codebook increases, the more the searching time reduction also increases.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2
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• pp.129-134
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• 2003

In this paper, we efficiently implement the AMR speech coder by reducing the complexity of algebraic codebook search. To reduce the computational complexity of the algebraic codebook search, we propose a fast algebraic codebook search method that improves conventional depth first tree search method used in AMR speech coder algorithm. The proposed method reduces the search complexity by pruning the trees which are less possible to be selected as an optimum excitation. This method needs no additional computation for selecting the trees to be pruned and reduces the computational complexity considerably compared to the original depth first tree search method with slightly degradation or speech qualify. Applying our method to the implementation or AMR speech coder with 12.2 kbps mode by using the TeakLite DSP, we reduce the search complexity about 40% compared to the conventional method.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.449-455
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• 2014

Detection of moving objects is a fundamental task in most of the computer vision applications, such as video surveillance, activity recognition and human motion analysis. This is a difficult task due to many challenges in realistic scenarios which include irregular motion in background, illumination changes, objects cast shadows, changes in scene geometry and noise, etc. In this paper, we propose an foreground extraction algorithm based on codebook, a database of information about background pixel obtained from input image sequence. Initially, we suppose a first frame as a background image and calculate difference between next input image and it to detect moving objects. The resulting difference image may contain noises as well as pure moving objects. Second, we investigate a codebook with color and brightness of a foreground pixel in the difference image. If it is matched, it is decided as a fault detected pixel and deleted from foreground. Finally, a background image is updated to process next input frame iteratively. Some pixels are estimated by input image if they are detected as background pixels. The others are duplicated from the previous background image. We apply out algorithm to PETS2009 data and compare the results with those of GMM and standard codebook algorithms.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4
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• pp.308-314
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• 2003

Wideband speech communications with 7㎑ bandwidth can provide high-quality speech services that are almost impossible with current narrow-band speech communications with 3.4 ㎑ bandwidth, and AMR wideband codec was recently developed for these services. The performance of AMR wideband codec is excellent due to its wideband information and partially to ACELP structure, but it requires high computational complexity especially in codebook search. In this paper, to solve this problem, an efficient codebook search method for AMR wideband codec is proposed. The proposed method first determines the coarse initial codevector, then improves the performance of codevector by replacing a poor pulse in codevector with better one iteratively. Simulations show that AMR wideband codec with proposed codebook search method has higher performance with much less computational cost than conventional AMR wideband codec.

• The Journal of the Acoustical Society of Korea
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• v.23 no.8
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• pp.583-589
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• 2004

Proposed is a speaker normalization method based on vector quantizer for continuous speech recognition (CSR) system in which no acoustic information is made use of. The proposed method, which is an improvement of the previously reported speaker normalization scheme for a simple digit recognizer, builds up a canonical codebook by iteratively training the codebook while the size of codebook is increased after each iteration from a relatively small initial size. Once the codebook established, the warp factors of speakers are estimated by comparing exhaustively the warped versions of each speaker's utterance with the codebook. Two sets of phones are used to estimate the warp factors: one, a set of vowels only. and the other, a set composed of all the Phonemes. A Piecewise linear warping function which corresponds to the estimated warp factor is adopted to warp the power spectrum of the utterance. Then the warped feature vectors are extracted to be used to train and to test the speech recognizer. The effectiveness of the proposed method is investigated by a set of recognition experiments using the TIMIT corpus and HTK speech recognition tool kit. The experimental results showed comparable recognition rate improvement with the formant based warping method.

• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.107-112
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• 1996

In this paper we propose a new fast codebook training algorithm for reducing the searching time of LBG algorithm. For each training data, the proposed algorithm stores the indexes of codewords that are close to that training data in the first iteration. It reduces computation time by searching only those codewords, the indexes of which are stored for each training data. Compared to one of the previous fast training algorithm, FSLBG, it obtains a better codebook with less exccution time. In our experiment, the performance of the codebook generated by the proposed algorithm in terms of peak signal-to-noise ratio(TSNR) is very close to that of LBG algorithm. However, the codewords to be searched for each training data of the proposed algorithm is only about 6%, for a codebook size of 256 and 1.6%, for a codebook size of 1.24, of LBG algorithm.