• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.75-82
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• 2012

The Photoplethysmogram is a similar periodic signal that synchronized to a heartbeat. In this paper, we propose a periodic moving average filter that use similarity of Photoplethysmogram. This filtering method has the average value of each samples through separating the cycle of PPG signal. If there are some motion artifacts in continuous PPG signal, disjoin the signal based on cycle. And then, we made these signals to have same cycle by coordinating the number of sample. After arrange these cycles in 2 dimension, we put the average value of each samples from starting till now. So, we can eliminate the motion artifacts without damaged PPG signal.

• Journal of the Korean Magnetics Society
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• v.26 no.3
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• pp.81-85
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• 2016

This paper introduces a performance integration method to predict variation characteristic of a performance function of electromagnetic machines or devices due to manufacturing tolerances. A normalized performance function space and a hybrid mean value technique are adapted to effectively predict mean and variance, which can identify probabilistic distribution of the performance function. To verify the effectiveness and accuracy of the proposed method, a mathematical problem and a loudspeaker model are tested, and numerical results are compared with those of existing methods such as Monte Carlo simulation and univariate dimension reduction method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.687-692
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• 2006

In a conventional ICA(Independent Component Analysis) based face recognition method, PCA(Principal Component Analysis) first is used for feature extraction, ICA learning method then is applied for feature enhancement in the reduced dimension. It is not considered that a necessary component can be located in the discarded feature space. In the new ICA(NICA), learning extracts features using the magnitude of kurtosis (4-th order central moment or cumulant). But, the pure ICA method can not discard noise effectively. The synergy effect of PCA and ICA can be achieved if PCA is used for noise reduction filter. Namely, PCA does whitening and noise filtering. ICA performs feature extraction. Experiment results show the effectiveness of the new ICA method compared to the conventional ICA approach.

• Korean Journal of Computational Design and Engineering
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• v.14 no.5
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• pp.297-305
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• 2009

Automatic generation of the mid-surfaces of a CAD model is becoming a useful function in that it can help increase the efficiency of engineering analysis as far as it does not affect the result seriously. Several methods had been proposed previously to automatically generate the mid-surfaces, but they often failed to generate the mid-surfaces of complex CAD models. Due to the inherent difficulty of this mid-surface generation problem, it may not be possible to come up with a complete and general method to solve this problem. Since a method that can handle a specific case may not work for different cases, it seems that developing case-specific methods ends up with solving only a fraction of the problem. In this paper, therefore, we propose a method to generate mid-surfaces based on a divide-and-conquer paradigm. This method first decomposes a complex CAD model into simple volumes. The mid-surfaces of the simple volumes are automatically generated by the existing methods, and then they are converted into the mid-surfaces of the original CAD model.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.91-96
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• 2015

In this study, we introduce robust face recognition system with illumination variation realized with the aid of CT preprocessing method. As preprocessing algorithm, Census Transform(CT) algorithm is used to extract locally facial features under unilluminated condition. The dimension reduction of the preprocessed data is carried out by using $(2D)^2$PCA which is the extended type of PCA. Feature data extracted through dimension algorithm is used as the inputs of proposed radial basis function neural networks. The hidden layer of the radial basis function neural networks(RBFNN) is built up by fuzzy c-means(FCM) clustering algorithm and the connection weights of the networks are described as the coefficients of linear polynomial function. The essential design parameters (including the number of inputs and fuzzification coefficient) of the proposed networks are optimized by means of artificial bee colony(ABC) algorithm. This study is experimented with both Yale Face database B and CMU PIE database to evaluate the performance of the proposed system.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.275-279
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• 2013

Recently, as multimedia information becomes popular, there are many studies to retrieve images based on images in the web. However, it is hard to find the matching images which users want to find because of various patterns in images. In this paper, we suggest an efficient images retrieval system based on images for finding products in internet shopping malls. We extract features for image retrieval by using SIFT (Scale Invariant Feature Transform) algorithm, repeat keypoint matching in various dimension by using PCA-SIFT, and find the image which users search for by combining them. To verify efficiency of the proposed method, we compare the performance of our approach with that of SIFT and PCA-SIFT by using images with various patterns. We verify that the proposed method shows the best distinction in the case that product labels are not included in images.

• Journal of the Korean Society for Precision Engineering
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• v.3 no.3
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• pp.40-71
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• 1986

By developing a computer program for the systematic design of worm gears, the design formulae and tables of AGMA, JGMA, BS and DIN are analized and compared. The computer program can be used on micro-computers. According to the input data of the reduction ratio, the center distance. the driving torque and the material as design parameters, the program calculate the most efficient worm gear dimension. The variation of the design parameters and other empirical coefficients in case of resulting an inadequate design gear dimension can be easily modified throuth the way of interactive method between the user and the monitoring system of computer. A proposal of the standardization of worm gears was made in which a standard module according to the DIN 323 standard series number was applied. For the more exact and effective calculation of the stress concentration and the deformation of gear teeth, a computer program using the boundary element method is also developed. Even the strength of the special gear shape such as Niemann's "Cavex" gear can be calculated in a short CPU-time. The most effort of this study has been layed on the developing a computer program for the correction of a tooth profile and face width which is most important design factor for an exact and wide teeth contacts under loads, especially by great and wide gears. For this purpose were investigated the tooth stiffness, the mesh interferences and the kinematics and the dynamics of gear mesh. The deflection and the deformation of the gear shaft due to the loads acting on gear and shaft were aslo considered. Some examples have shown the sufficient good status of teeth contact in which the correction of the tooth profile and face width were accomplished due to the calculated results.d results.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.539-544
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• 2013

In this paper, we was designed three-dimensional face recognition algorithm using polynomial based RBFNNs and proposed method to calculate the recognition performance. In case of two-dimensional face recognition, the recognition performance is reduced by the external environment like facial pose and lighting. In order to compensate for these shortcomings, we perform face recognition by obtaining three-dimensional images. obtain face image using three-dimension scanner before the face recognition and obtain the front facial form using pose-compensation. And the depth value of the face is extracting using Point Signature method. The extracted data as high-dimensional data may cause problems in accompany the training and recognition. so use dimension reduction data using PCA algorithm. accompany parameter optimization using optimization algorithm for effective training. Each recognition performance confirm using PSO, DE, GA algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.897-904
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• 2005

Face Recognition has been an active research area because it is not difficult to acquire face image data and it is applicable in wide range area in real world. Due to the high dimensionality of a face image space, however, it is not easy to process the face images. In this paper, we propose a method to reduce the dimension of the facial data and extract the features from them. It will be solved using the method which extracts the features from holistic face images. The proposed algorithm consists of two parts. The first is the using of principal component analysis (PCA) to transform three dimensional color facial images to one dimensional gray facial images. The second is integrated linear discriminant analusis (PCA+LDA) to prevent the loss of informations in case of performing separated steps. Integrated LDA is integrated algorithm of PCA for reduction of dimension and LDA for discrimination of facial vectors. First, in case of transformation from color image to gray image, PCA(Principal Component Analysis) is performed to enhance the image contrast to raise the recognition rate. Second, integrated LDA(Linear Discriminant Analysis) combines the two steps, namely PCA for dimensionality reduction and LDA for discrimination. It makes possible to describe concise algorithm expression and to prevent the information loss in separate steps. To validate the proposed method, the algorithm is implemented and tested on well controlled face databases.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.239-243
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• 2004

It does not exist almost that Most satellite image has both high spectral and spatial resolution. In order to apply the satellite image for to be actual, we need numerical and analytical technique development to improve the resolution. Specially in the function of solid illustration, we represent the solid image through the image generation to solid screen. The main function includes magnification, reduction, screen center movement, Panning, territory magnification. The method to process the image includes histogram and contrast modulation. Afterwards, we will develop the function includes 3-dimension cursor to control the elevation position and calculate the ground coordination automatically. There is the layer control includes the representation and the edition of 3D vector, extraction the Z value by On the Ground and digital elevation.