• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.138-146
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• 1996

In this paper, w epropose a new mehtod to represent the shape and to recognize the object. The shape description and the matching is implemented by using the distance transform on the morphological skeleton. The employed distance transform is the chamfer (3,4) distance transform, because the chamfer distance transform (CDT) has an approximate value to the euclidean distance. The 2-D object can be represented by means of the distribution of the distance transform on the morphological skeleton, the number of skeletons, the sum of the CDT, and the other features are employed as the mtching parameters. The matching method has the invariant features (rotation, translation, and scaling), and then the method is used effectively for recognizing the differently-posed objects and/or marks of the different shape and size.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.281-286
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• 2003

Wavelet Transform can effectively represent the local characteristics of a signal in the space-frequency domain. However, the feature vector extracted using wavelet transform is not translation invariant. This paper describes a new feature extraction method using wavelet transform, which is translation-invariant. Based on this translation-invariant feature extraction, the iris recognition method, based on this feature extraction method, is robust to noises. Experimentally, we show that the proposed method produces super performance in iris recognition.

• Journal of Information Processing Systems
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• v.8 no.1
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• pp.85-100
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• 2012

The Hartley transform based feature extraction method is proposed for fingerprint matching. Hartley transform is applied on a smaller region that has been cropped around the core point. The performance of this proposed method is evaluated based on the standard database of Bologna University and the database of the FVC2002. We used the city block distance to compute the similarity between the test fingerprint and database fingerprint image. The results obtained are compared with the discrete wavelet transform (DWT) based method. The experimental results show that, the proposed method reduces the false acceptance rate (FAR) from 21.48% to 16.74 % based on the database of Bologna University and from 31.29% to 28.69% based on the FVC2002 database.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2620-2623
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• 2000

The standard approach consists of using correlation of orthogonal functions in digital filtering, such as well-known FFT(Fast Fourier Transform) and FWT(Fast Walsh Transform). But it needs much calculations, multiplications and additions. The calculation amount is m $log_2m$ in the general case. Therefore, this requires high speed processors to calculate in real time, which can calculate floating point. This study developed improved fast Walsh transform based on dyadic-ordered fast Walsh transform, then regenerated signal flow graph of improved fast Walsh transform, and used it for digital filtering, and then measured fundamental frequency and harmonics for current and voltage signals of power system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.5
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• pp.905-913
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• 1987

This paper presents a speaker dependent isolated digit recognition algorithm using the Mellin transform. Since the Mellin transform converts a scale information into a phase information, attempts have been made to utilize this scale invariance property of the Mellin transform in order to alleviate a time-normalization procedure required for a speech recognition. It has been found that good results can be obtained by taking the Mellin transform to the features such as a ZCR, log energy, normalized autocorrelation coefficients, first predictor coefficient and normalized prediction error. We employed a difference function for evaluating a similarity between two patterns. When the proposed algorithm was tested on Korean digit words, a recognition rate of 83.3% was obtained. The recognition accuracy is not compatible with the other technique such as LPC distance however, it is believed that the Mellin transform can effectively perform the time-normalization processing for the speech recognition.

• Aerospace Engineering and Technology
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• v.9 no.1
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• pp.98-105
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• 2010

Fast Fourier Transform is the fast implementation of Discrete Fourier Transform, which deletes periodic operation of DFT. According to the definition, radix-2 FFT can be implemented byre cursive call which divides the input signal points into 2 signal points. Because of its time-consuming stack-copy operation, this recursive method is very slow. To overcome this drawback, butterfly operation with signal rearrangement was devised. Based on the ideas of signal rearrangement and butterfly operation, this paper applies the signal rearrangement method to the Radix-3 FFT and checks the validity of this method.

• Journal of the Korean Chemical Society
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• v.37 no.4
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• pp.371-377
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• 1993

Fourier Transform UV/VIS spectrometer has been modified for emission spectroscopy with the technique of supersonic expansion, in which the unstable molecular radical $CH_3S$ has been generated in a jet by a high voltage DC discharge. The fluorescence spectra of the supersonically cooled radical have been recorded on a Fourier Transform UV/VIS spectrometer. The ratio of signal to noise of the spectra has been improved substantially. Also the rotational structure has been clearly resolved for $CH_3S$ molecular radical.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.657-663
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• 2012

Recently, by increasing of devices which are sensitive to power quality, the deterioration of power quality has been accelerated. For this reason, the social and economic losses are increased. So not only correct measurement and evaluation, but also countermeasure for improvement of power quality is surely necessary for both electric power supplier and consumer. In this paper, the discrimination algorithm for events and variation occurred in distribution systems using S-transform is proposed. Firstly, we review for events and variations that occur in distribution system. Next, we simulate events and variations on various conditions using ElectroMagnetic Transient Program(EMTP). For the simulation, the IEEE 13 Node Test Feeder and KEPCO's distribution system is modeled. Finally, for the analysis, a modified wavelet transform known as S-transform is adopted to find out the characteristics of each events and variations.

• Nuclear Engineering and Technology
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• v.39 no.3
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• pp.221-230
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• 2007

Wavelet theory was applied to detect a singularity in a reactor power signal. Compared to Fourier transform, wavelet transform has localization properties in space and frequency. Therefore, using wavelet transform after de-noising, singular points can easily be found. To test this theory, reactor power signals were generated using the HANARO(a Korean multi-purpose research reactor) dynamics model consisting of 39 nonlinear differential equations contaminated with Gaussian noise. Wavelet transform decomposition and de-noising procedures were applied to these signals. It was possible to detect singular events such as a sudden reactivity change and abrupt intrinsic property changes. Thus, this method could be profitably utilized in a real-time system for automatic event recognition(e.g., reactor condition monitoring).

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1331-1344
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• 2017

In this paper, data hiding algorithm using Discrete Wavelet Transform (DWT) and Arnold Transform is proposed. The secret data is scrambled using Arnold Transform to make it secure. Wavelet subbands of a cover image are obtained using DWT. The scrambled secret data is embedded into significant wavelet coefficients of subbands of a cover image. The proposed algorithm is robust to a variety of attacks like JPEG and JPEG2000 compression, image cropping and median filtering. Experimental results show that the PSNR of the composite image is 1.05 dB higher than the PSNR of existing algorithms and capacity is 25% higher than the capacity of existing algorithms.