• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.799-807
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• 2004

In this paper, we deal with an emotion recognition method using facial images and speech signal. Six basic human emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. Emotion recognition using the facial expression is performed by using a multi-resolution analysis based on the discrete wavelet transform. And then, the feature vectors are extracted from the linear discriminant analysis method. On the other hand, the emotion recognition from speech signal method has a structure of performing the recognition algorithm independently for each wavelet subband and then the final recognition is obtained from a multi-decision making scheme.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.157-165
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• 2013

In this paper, efficient digit-serial VLSI architecture for 1D (9,7) lifting-based discrete wavelet transform (DWT) filter has been proposed. The proposed architecture computes the DWT in digit basis, so that the required hardware is reduced. Also, the multiplication is replaced with the shift and add operation to minimize the hardware requirement. Bit allocation for input, output, and the internal data has been determined by analyzing the PSNR. We have carefully designed the data feedback latency not to degrade the performance in the recursive folded scheduling. The proposed digit-serial architecture requires small amount of hardware but achieve 100% of hardware utilization, so we try to optimize the tradeoffs between the hardware cost and the performance. The proposed architecture has been designed and verified by VerilogHDL and synthesized by Synopsys Design Compiler with a DongbuHitek $0.18{\mu}m$ STD cell library. The maximum operating frequency is 330MHz with 3,770 gates in equivalent two input NAND gates.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.6
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• pp.59-68
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• 2002

In this paper, we design the two-dimensional Discrete Wavelet Transform (2D DWT) filter that is widely used in various applications such as image compression because it has no blocking effects and relatively high compression rate. The filter that we used here is two-channel four-taps QMF(Quadrature Mirror Filter) Lattice filter with PR (Perfect Reconstruction) property. The proposed DWT architecture, with two consecutive inputs shows an efficient performance with a minimum of such hardware resources as multipliers, adders, and registers due to a simple scheduling. The proposed architecture was verified by the RTL simulation, and utilizes the hardware 100%. Our architecture shows a relatively high performance with a minimum hardware when compared with other approaches. An efficient memory mapping and address generation techniques are introduced and the fixed-point arithmetic analysis for minimizing the PSNR degradation due to quantization is discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.573-580
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• 2005

In this paper, we propose an emotion recognition using static and dynamic facial images to effectively design human interface. The proposed method is constructed by HMM(Hidden Markov Model), PCA(Principal Component) and wavelet transform. Facial database consists of six basic human emotions including happiness, sadness, anger, surprise, fear and dislike which have been known as common emotions regardless of nation and culture. Emotion recognition in the static images is performed by using the discrete wavelet. Here, the feature vectors are extracted by using PCA. Emotion recognition in the dynamic images is performed by using the wavelet transform and PCA. And then, those are modeled by the HMM. Finally, we obtained better performance result from merging the recognition results for the static images and dynamic images.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.94-102
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• 2011

To alleviate the size and bandwidth requirement in JPEG2000 system, a new Embedded Compression(EC) algorithm with minor image quality drop is proposed. For both random accessibility and low latency, very simple and efficient hadamard transform based compression algorithm is devised. We reduced LL intermediate memory and code-block memory to about half size and achieved significant memory bandwidth reductions(about 52~73%) through proposed multi-mode algorithms, without requiring any modification in JPEG2000 standard algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4A
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• pp.336-344
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• 2005

Discrete Wavelet Transform(DWT) is the oncoming generation of compression technique that has been selected for MPEG4 and JEPG2000, because it has no blocking effects and efficiently determines frequency property of temporary time. In this paper, we propose an efficient bit-serial architecture for the low-power and low-complexity DWT filter, employing two-channel QMF(Qudracture Mirror Filter) PR(Perfect Reconstruction) lattice filter. The filter consists of four lattices(filter length=8) and we determine the quantization bit for the coefficients by the fixed-length PSNR(peak-signal-to-noise ratio) analysis and propose the architecture of the bit-serial multiplier with the fixed coefficient. The CSD encoding for the coefficients is adopted to minimize the number of non-zero bits, thus reduces the hardware complexity. The proposed folded 1D DWT architecture processes the other resolution levels during idle periods by decimations and its efficient scheduling is proposed. The proposed architecture requires only flip-flops and full-adders. The proposed architecture has been designed and verified by VerilogHDL and synthesized by Synopsys Design Compiler with a Hynix 0.35$\mu$m STD cell library. The maximum operating frequency is 200MHz and the throughput is 175Mbps with 16 clock latencies.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.362-368
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• 2009

Electrical fires have been occurred continuously in spite of installing ELB. Therefore the concern with the electrical arc-fault that cause the fire has growing. This paper measured series arc fault currents by the method of arc generator test in UL standard 1699. The used analysis methods in this paper are three different ways using DWT(discrete wavelet transform) those are frequently used for the arc fault current signal analysis. The arc fault detection probability is 100 % by method using noise-energy/shoulder-duration ratio of approximation coefficient. As these results, the variation of noise-energy and shoulder-duration ratio of approximation coefficient are founded important factors for the analysis of arc fault.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.1
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• pp.84-92
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• 2001

In this papers, we proposed the new method in order to diagnosis aging state of transformers. For wavelet transform, Daubechies filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion skewness, kurtosis) about each acoustic emission signal. Also, these coefficients are used to identify normal and fault signal of internal partial discharge in transformer. As improved method for classification use neural network. Extracted statistical parameters are input into an back-propagation neural network. The number of neurons of hidden layer are obtained through Result of Cross-Validation. The network, after training, can decide whether the test signal is early aging state, alst aging state or normal state. In quantity analysis, capability of proposed method is superior to compared that of classical method.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.50 no.3
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• pp.121-129
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• 2001

In this paper, a new efficient feature extraction method based on Daubechies discrete wavelet transform is presented. This paper especially deals with the assessment of process statistical parameter using the features extracted from the wavelet coefficients of measured acoustic emission signals. Since the parameter assessment using all wavelet coefficients will often turn out leads to inefficient or inaccurate results, we selected that level-3 stage of multi decomposition in discrete wavelet transform. We make use of the feature extraction parameter namely, maximum value of acoustic emission signal, average value, dispersion, skewness, kurtosis, etc. The effectiveness of this new method has been verified on ability a diagnosis transformer go through feature extraction in stage of aging(the early period, the middle period, the last period)

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.11
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• pp.993-1000
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• 2012

In this research, we proposed an efficient VLSI architecture of the lifting-based 2D DWT (Discrete Wavelet Transform) filter with 100% hardware utilization. The (9,7) filter structure has been applied and extendable to the filter length. We proposed a new block-based scheduling that computes the DWT for the lower levels on an "as-early-as-possible" basis, which means that the calculation for the lower level will start as soon as the data is ready. Since the proposed 2D DWT computes the outputs of all levels by one row-based scan, the intermediate results for other resolution levels should be kept in storage such as the Data Format Converter (DFC) and the Delay Control Unit (DCU) until they are used. When the size of input image is $N{\times}N$ and m is the filter length, the required storage for the proposed architecture is about 2mN. Since the proposed architecture processes the 2D DWT in horizontal and vertical directions at the same time with 4 input data, the total period for 2D DWT is $N^2(1-2^{-2J})/3$.