• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.1
• /
• pp.25-31
• /
• 2005

In this paper, we present a face detection system using the Support Vector Domain Description (SVDD) in color images. Conventional face detection algorithms require a training procedure using both face and non-face images. In SVDD however we employ only face images for training. We can detect faces in color images from the radius and center pairs of SVDD. We also use Entropic Threshold for extracting the facial feature and sliding window for improved performance while saving processing time. The experimental results indicate the effectiveness and efficiency of the proposed algorithm compared to conventional PCA (Principal Component Analysis)-based methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.7
• /
• pp.1439-1446
• /
• 2011

This paper describes the algorithm that lowers the dimension, maintains the object recognition and significantly reduces the eigenspace configuration time by combining the higher correlation feature information and Principle Component Analysis. Since the suggested method doesn't require a lot of computation than the method using existing geometric information or stereo image, the fact that it is very suitable for building the real-time system has been proved through the experiment. In addition, since the existing point to point method which is a simple distance calculation has many errors, in this paper to improve recognition rate the recognition error could be reduced by using several successive input images as a unit of recognition with K-Nearest Neighbor which is the improved Class to Class method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2006.06a
• /
• pp.505-506
• /
• 2006

PD(partial discharge) occurred from variable PD sources in air may be the cause of breakdown in high voltage equipment which affect huge outage in power system. Identification and localization of PD sources is very important for engineer to cope with huge accident beforhand. PD phenomena can be detected by acoustic emission sensor or electromagnetic sensor like antenna. This paper has investigated the identification method using PCA(principal component analysis) for the PD signals from variable PD sources, for which the electric field distribution and PD inception voltages were simulated by using commercial FEM program. PD signals was detected by ultra wideband antenna. Their own features were extracted as the frequency coefficients transformed with FFT(fast fourier transform) and used to obtain independent pincipal components of each PD signals.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.8 no.6
• /
• pp.111-117
• /
• 2008

In this paper, we describes the boxing motion recognition which is used in the part of games, animation. To recognize the boxing motion, we have used two algorithms, one is principle component analysis, the other is dynamic time warping algorithm. PCA is the simplest of the true eigenvector-based multivariate analyses and often used to reduce multidimensional data sets to lower dimensions for analysis. DTW is an algorithm for measuring similarity between two sequences which may vary in time or speed. We introduce and compare PCA and DTW algorithms respectively. We implemented the recognition of boxing motion on the motion capture system which is developed in out research, and depict the system also. The motion graph will be created by boxing motion data which is acquired from motion capture system, and will be normalized in a process. The result has implemented in the motion recognition system with five actors, and showed the performance of the recognition.

• Analytical Science and Technology
• /
• v.24 no.2
• /
• pp.85-93
• /
• 2011

To protect the steel structure in a high story buildings from fire, the sprayed fire-resistive materials are applied during the construction. Current standard methods to check the quality of sprayed fire-resistive materials are real fire test in lab, which take a long time (several weeks) and expensive. In this study, a simple analytical method to check the quality of sprayed fire-resistive materials is developed using Near Infrared Spectroscopy (NIR). Total 9 kinds of sprayed fire-resisted materials and 3 kinds of normal sprayed material sets were used for the analysis. Each set of materials was 50 to 100 samples. Samples are grinded and make a fine powder. The spectral data acquisition was carried out using FT-NIR spectrometer with a integrating sphere. NIR methods successfully identify the sprayed fire resistive materials by a principle component analysis (PCA) after a vector normalization (SNV) pretreatment.

• Interdisciplinary Bio Central
• /
• v.6 no.4
• /
• pp.3.1-3.10
• /
• 2014

Amino acid substitution matrices are essential tools for protein sequence analysis, homology sequence search in protein databases and multiple sequence alignment. The PAM matrix was the first widely used amino acid substitution matrix. The BLOSUM series then succeeded the PAM matrix. Most substitution matrixes were developed by using the statistical frequency of substitution between each amino acid at blocks representing groups of protein families or related proteins. However, substitution of amino acids is based on the similarity of physiochemical properties of each amino acid. In this study, a new approach was used to obtain major physiochemical properties in multiple sequence alignment. Frequency of amino acid substitution in multiple sequence alignment database and selected attributes of amino acids in physiochemical properties database were merged. This merged data showed the major physiochemical properties through principle components analysis. Using factor analysis, these four principle components were interpreted as flexibility of electronic movement, polarity, negative charge and structural flexibility. Applying these four components, BAPS was constructed and validated for accuracy. When comparing receiver operated characteristic ($ROC_{50}$) values, BAPS scored slightly lower than BLOSUM and PAM. However, when evaluating for accuracy by comparing results from multiple sequence alignment with the structural alignment results of two test data sets with known three-dimensional structure in the homologous structure alignment database, the result of the test for BAPS was comparatively equivalent or better than results for prior matrices including PAM, Gonnet, Identity and Genetic code matrix.

• Journal of Korea Multimedia Society
• /
• v.22 no.12
• /
• pp.1347-1355
• /
• 2019

Deep learning approach based on convolution neural network (CNN) has extensively studied in the field of computer vision. However, periocular feature extraction using CNN was not well studied because it is practically impossible to collect large volume of biometric data. This study uses the ResNet model which was trained with the ImageNet dataset. To overcome the problem of insufficient training data, we focused on the training of multi-layer perception (MLP) having simple structure rather than training the CNN having complex structure. It first extracts features using the pretrained ResNet model and reduces the feature dimension by principle component analysis (PCA), then trains a MLP classifier. Experimental results with the public periocular dataset UBIPr show that the proposed method is effective in person authentication using periocular region. Especially it has the advantage which can be directly applied for other biometric traits.

• Proceedings of the KIEE Conference
• /
• 2004.07d
• /
• pp.2441-2443
• /
• 2004

This paper presents a method that a mobile robot finds location of doors in complex environments and safely traverses the door. A robot must be able to find the door in order that it achieves the behavior that is scheduled after traversing a door. PCA(Principle Component Analysis) algorithm using the vision is used for a robot to find the positions of door. Fuzzy controller using sonar data is used for a robot to avoid a obstacle and traverse the doors.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.869-870
• /
• 2008

Illumination variation is the most significant factor affecting face recognition rate. In this paper, we propose adaptive smoothing based on combined most significant bit (CMSB) - plane and local entropy for robust face recognition in varying illumination. Illumination normalization is achieved based on Retinex method. The proposed method has been evaluated based on the CMU PIE database by using Principle Component Analysis (PCA).

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2008.04a
• /
• pp.435-438
• /
• 2008

본 논문에서는 애니메이션을 위해서 얼굴의 특징표현(Action Units)의 조합하는 방법으로 얼굴 모델링을 하기 위한 3D대응점(3D dense correspondence)을 찾는 방법을 제시한다. AUs는 표정, 감정, 발음을 나타내는 얼굴의 특징표현으로 통계적 방법인 PCA (Principle Component Analysis)를 이용하여 만들 수 있다. 이를 위해서는 우선 3D 모델상의 대응점을 찾는 것이 필수이다. 2D에서 얼굴의 주요 특징 점은 다양한 알고리즘을 이용하여 찾을 수 있지만 그것만으로 3D상의 얼굴 모델을 표현하기에는 적합하지 않다. 본 논문에서는 3D 얼굴 모델의 대응점을 찾기 위해 원기둥 좌표계 (Cylinderical Coordinates System)을 이용하여 3D 모델을 2D로 투사(Projection)시켜서 만든 2D 이미지간의 워핑(Warping) 을 통한 대응점을 찾아 역으로 3D 모델간의 대응점을 찾는다. 이것은 3D 모델 자체를 변환하는 것보다 적은 연산량으로 계산할 수 있고 본래 형상의 변형이 없다는 장점을 가지고 있다.