• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1140-1145
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• 2003

Image normalization is one of the important areas in pattern recognition. Also, log-polar images are useful in the sense that their image data size is reduced dramatically comparing with conventional images and it is possible to develop faster pattern recognition algorithms. Especially, the log-polar image is very similar with the structure of human eyes. However, there are almost no researches on pattern recognition using the log-polar images while a number of researches on visual tracking have been executed. We propose an image normalization technique of log-polar images using momentums applicable for affine-invariant pattern recognition. We handle basic distortions of an image including translation, rotation, scaling, and skew of a log-polar image. The algorithm is experimented in a PC-based real-time vision system successfully.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.267-271
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• 2002

The Hotelling transform is based on statistical properties of an image. The principal uses of this transform are in data compression. The basic concept of the Hotelling transform is that the choice of basis vectors pointing the direction of maximum variance of the data. This property can be used for rotation normalization. Many objects of interest in pattern recognition applications can be easily standardized by performing a rotation normalization that aligns the coordinate axes with the axes of maximum variance of the pixels in the object. However, this transform can not be used to rotation normalization of color images directly. In this paper, we propose a new method for rotation normalization of color images based on the Hotelling transform. The Hotelling transform is performed to calculate basis vectors of each channel. Then the summation of vectors of all channels are processed. Rotation normalization is performed using the result of summation of vectors. Experimental results showed the proposed method can be used for rotation normalization of color images effectively.

• Genomics & Informatics
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• v.2 no.2
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• pp.92-98
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• 2004

A cDNA microarray experiment is one of the most useful high-throughput experiments in medical informatics for monitoring gene expression levels. Statistical analysis with a cDNA microarray medical data requires a normalization procedure to reduce the systematic errors that are impossible to control by the experimental conditions. Despite the variety of normalization methods, this. paper suggests a more general and synthetic normalization algorithm with a control gene set based on previous studies of normalization. Iterative normalization method was used to select and include a new control gene set among the whole genes iteratively at every step of the normalization calculation initiated with the housekeeping genes. The objective of this iterative normalization was to maintain the pattern of the original data and to keep the gene expression levels stable. Spatial plots, M&A (ratio and average values of the intensity) plots and box plots showed a convergence to zero of the mean across all genes graphically after applying our iterative normalization. The practicability of the algorithm was demonstrated by applying our method to the data for the human photo aging study.

• The Journal of the Acoustical Society of Korea
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• v.3 no.1
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• pp.25-35
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• 1984

This paper analysis the Dynamic Time Warping algorithms for time normalization of speech pattern and discusses the Dynamic Programming algorithm for spoken Korean isolated digits recognition. In the DP matching, feature vectors of the reference and test pattern are consisted of first three formant frequencies extracted by power spectrum density estimation algorithm of the ARMA model. The major differences in the various DTW algorithms include the global path constrains, the local continuity constraints on the path, and the distance weighting/normalization used to give the overall minimum distance. The performance criterias to evaluate these DP algorithms are memory requirement, speed of implementation, and recognition accuracy.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1997.11a
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• pp.451-455
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• 1997

The partial discharge has been blown as the chief breakdown of power equipments. The analysis and the recognition is much difficult because the partial discharge signal is very small and has complex aging pattern. Recently, insulation aging diagnosis based on pattern of phase(Ф), partial discharge magnitude(q), number(n) has been very important. Owing to depreciate the reappearance of aging progress at the electrical tree pattern and to be difficult to analyze visually, the study on partial discharge pattern is suggested to normalizing analysis method of partial discharge signals. This parer is purposed on prediction of life-time measurement of cv-cable, on decision of risk degree with normalization and real-time measurement of partial discharge signals for aging diagnosis of cv-cable. As normalizing the aging signals of electrical tree in cv-cable, it is able to confirm risk degree of insulation material with the distribution of Ф-q-n and recognize the process of aging pattern using neural network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.5
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• pp.332-339
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• 1986

This paper proposes a new method for the normalization of shape pattern based on Gaussian probability density function to increase automatic recognition rate of hand-written Hangul pattern. The sizes of hand-written Hangul pattern are detected from the input images, and pattern sizes are normalized by two variables interpolation. The pattrn shapes are noralized by letting correlation coefficients equal to zero. It is analyzed theoretically and verified through computer simulation for the relation between input image and normaized shape pattern. It is confirmed that this method is effective and reasonable for deformed hand-written Hangul pattern. Experimental resu results show that the declination. size and stroke width of hand-written Hangul patterns are mych improved.

• Proceedings of the KIEE Conference
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• 2004.05b
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• pp.109-112
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• 2004

In this study, the applicability of SOM(Self Organizing Map) algorithm to partial discharge pattern recognition have been investigated. For the purpose, using acquired data from the artificial defects in GIS, SOM algorithm which has some advantages such as data accumulation ability and the degradation trend trace ability was compared with conventionally used BP(Back Propagation) algorithm. As a result, basically BP algorithm was found out to be better than SOM algorithm. Therefore, it is needed to apply SOM algorithm in combination with BP algorithm in order to improve on-site applicability using the advantages of SOM. Also, for the pattern recognition by use of PRPDA(Phase Resolved Partial Discharge Analysis) it is required the normalization of the PRPDA graph. However, in case of the normalization both BP and SOM algorithm have shown worse results, so that it is required further study to solve the problem.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.04a
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• pp.99-101
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• 1986

• PNF and Movement
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• v.21 no.1
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• pp.87-94
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• 2023

Purpose: The present study aims to investigate the effects of a diagonal exercise pattern on selective activation of the upper extremity muscles using both normalization and isolation methods. Methods: In total, 17 asymptomatic subjects participated in this study. During the two diagonal patterns of exercise (diagonals 1 and 2), muscular activities of the upper trapezius (UT), lower trapezius (LT), serratus anterior (SA), anterior deltoid (AD), and infraspinatus (IS) were measured. The collected data were analyzed in two ways, according to the dominance of muscle activities (%Isolation) and according to normalized activities (%MVIC). Results: There were significant differences in LT, SA, AD, and IS between %MVIC and %Isolation (p<0.05), and the diagonal 1 pattern of exercise showed significantly more LT activities compared with the diagonal 2 pattern (p<0.05). Further, except for LT, there were no significant differences in muscle activities between the diagonal 1 and 2 exercises. Conclusion: The present study suggests that a diagonal pattern of exercise is advantageous for strengthening shoulder muscles, but caution is needed when applying to patients requiring selective strengthening. Regarding both the concentric and eccentric phases of exercise, there was no significant difference in muscular activation, except in LT, between the two diagonal patterns of exercises.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.3
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• pp.115-127
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• 2006

The purpose of this paper is evaluation of various normalization methods and fusion algorithms in addition to pattern classification algorithms for multi-biometric systems. Experiments are performed using various normalization functions, fusion algorithms and pattern classification algorithms based on Biometric Scores Set-Releasel(BSSR1) provided by NIST. The performance results are presented by Half Total Error Rate (WTER). This study gives base data for the study on performance enhancement of multiple-biometric system by showing performance results using single database and metrics.