• Title/Summary/Keyword: Principle component analysis(PCA)

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Positive and Negative Covariation Mechanism of Multiple Muscle Activities During Human Walking (보행 과정에서 발생하는 복합 근육 활성의 양성 및 음성 공변 메커니즘)

  • Kim, Yushin;Hong, Youngki
    • The Journal of the Korea Contents Association
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    • v.18 no.1
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    • pp.173-184
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    • 2018
  • In human walking, muscle co-contraction which produces simultaneous activities of multiple muscles is important in motor control mechanism of the central nervous system. This study aims to understand positive and negative covariation mechanism of inter-muscle activities during walking. In this study, we measured electromyography (EMG) in leg muscles. To identify motor modules, we recored EMG from 4 leg muscles bilaterally (the tibialis anterior, medial gastrocnemius, rectus femoris and medial hamstring muscles) and performed non-negative matrix factorization (NMF) and principa component analysis (PCA). Then, we computed covariation values from various combinations between muscles or motor modules and used two-way repeated measures analysis of variance to identify significantly different covariation patterns between muscle combinations. As the results, we found significant differences between covariation values of muscle combinations (p < 0.05). muscle groups within the same motor modules produced the positive covariations. However, there were strong negative covariation between motor modules. There was negative covariation in all muscle combination. Stable inter-module negative covariation suggests that motor modules may be the control unit in the complex motor coordination.

Studies on Genetic Diversity and Phylogenetic relationships of Chikso (Korea Native Brindle Cattle) Using the Microsatellite Marker (Microsatellite marker를 활용한 칡소의 유전적 다양성 및 유연관계 분석)

  • Choy, Yun Ho;Seo, Joo Hee;Park, Byungho;Lee, Seung Soo;Choi, Jae Won;Jung, Kyoung-sub;Kong, Hong Sik
    • Journal of Life Science
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    • v.25 no.6
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    • pp.624-630
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    • 2015
  • This study examined the genetic distance among Chikso (Korea native brindle cattle) in nine regional areas using allele frequencies and a genetic diversity analysis with microsatellite markers. The analysis of the genetic diversity and genetic relationships of 2068 Chikso (383 KW, 180 GG, 52 KN, 129 KB, 332 UL, 24 JN, 198 JB, 148 CN, 622 CB) was carried out using 11 microsatellite markers. The number of alleles, observed heterozygostiy (Hobs), expected heterozygosity (Hexp), and polymorphism information content (PIC) of the 11 microsatellite markers were 8–24, 0.672–0.834, 0.687–0.886, and 0.638–0.876, respectively. The expected probability of identity values in random individuals (PI), random half-sib (PIhalf-sibs), and random sibs (PIsibs) were estimated to be 5.24×10−19, 2.63×10−06, and 2.63× 10−06, respectively, indicating that these markers can be used for traceability systems in Chikso cattle. The results of a phylogenetic tree (neighbor-joining tree), principle component analysis (PCA), and factorial component analysis (FCA) revealed genetic distance among nine Chikso populations. In conclusion, this study provides useful basic data that can be utilized in Chikso breeding and development. In addition, we will have to manage and conserve as a valuable genetic resource, without losing diversity of Chikso.

Gesture Recognition Using Zernike Moments Masked By Duel Ring (이중 링 마스크 저니키 모멘트를 이용한 손동작 인식)

  • Park, Jung-Su;Kim, Tae-Yong
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.10
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    • pp.171-180
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    • 2013
  • Generally, when we apply zernike moments value for matching, we can use those moments value obtained from projecting image information under circumscribed circle to zernike basis function. However, the problem is that the power of discrimination can be reduced because hand images include lots of overlapped information due to its special characteristic. On the other hand, when distinguishing hand poses, information in specific area of image information except for overlapped information can increase the power of discrimination. In this paper, in order to solve problems like those, we design R3 ring mask by combining image obtained from R2 ring mask, which can weight information of the power of discrimination and image obtained from R1 ring mask, which eliminate the overlapped information. The moments which are obtained by R3 ring mask decrease operational time by reducing dimension through principle component analysis. In order to confirm the superiority of the suggested method, we conducted some experiments by comparing our method to other method using seven different hand poses.

Monthly Variation of n-alkanes concentration in PM2.5 of the Anmyeon Island (안면도 대기 중 PM2.5 내 n-alkanes의 월별 농도 분포 특성)

  • Kim, Ki Ae;Lee, Jong Sik;Kim, Eun Sil;Jung, Chang Hoon;Kim, Yong Pyo;Lee, Ji Yi
    • Journal of Korean Society for Atmospheric Environment
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    • v.34 no.1
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    • pp.166-176
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    • 2018
  • The n-alkanes which are stable compounds in the atmosphere are emitted by anthropogenic sources and biological sources. The goal of this study is to understand characteristics of n-alkane distributions in $PM_{2.5}$ of the Anmyeon Island which is one of background site in Korea. The concentration of n-alkanes in $PM_{2.5}$ was measured at Anmyeon Island for one year from June 2015 to May 2016. The average concentration of total n-alkanes (${\sum}$ n-alkanes) from C20 to C34 was $14.02{\pm}10.26ng\;m^{-3}$ and ranged from 1.77 to $47.65ng\;m^{-3}$. Various diagnostic parameters were used to identify the source. As a result, it is considered that Anmyeon Island had a large influence of biological sources during non-heating period, while the influence of anthropogenic emission during the heating period was significant. Principle Component Analysis (PCA) was performed and yielded three components that accounted for 93.6% of the total variance in n-alkanes. Factor 1, which accounted for 42.3% of the total variance, indicated anthropogenic source including fossil fuel and biomass combustion, while, Factor 3 was interpreted as the biological sources such as plant wax.

Fast Gabor Feature Extraction for Real Time Face Recognition (실시간 얼굴인식을 위한 빠른 Gabor 특징 추출)

  • Cho, Kyoung-Sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.597-600
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    • 2007
  • Face is considered to be one of the biometrics in person identification. But Face recognition is a high dimensional pattern recognition problem. Even low-resolution face images generate huge dimensional feature space. The aim of this paper is to present a fast feature extraction method for real time human face recognition. first, It compute eigen-vector and eigen-value by Principle component analysis on inputed human face image, and propose method of feature extraction that make feature vector by apply gabor filter to computed eigen-vector. And it compute feature value which multiply by made eigen-value. This study simulations performed using the ORL Database.

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A Secure Face Cryptogr aphy for Identity Document Based on Distance Measures

  • Arshad, Nasim;Moon, Kwang-Seok;Kim, Jong-Nam
    • Journal of Korea Multimedia Society
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    • v.16 no.10
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    • pp.1156-1162
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    • 2013
  • Face verification has been widely studied during the past two decades. One of the challenges is the rising concern about the security and privacy of the template database. In this paper, we propose a secure face verification system which generates a unique secure cryptographic key from a face template. The face images are processed to produce face templates or codes to be utilized for the encryption and decryption tasks. The result identity data is encrypted using Advanced Encryption Standard (AES). Distance metric naming hamming distance and Euclidean distance are used for template matching identification process, where template matching is a process used in pattern recognition. The proposed system is tested on the ORL, YALEs, and PKNU face databases, which contain 360, 135, and 54 training images respectively. We employ Principle Component Analysis (PCA) to determine the most discriminating features among face images. The experimental results showed that the proposed distance measure was one the promising best measures with respect to different characteristics of the biometric systems. Using the proposed method we needed to extract fewer images in order to achieve 100% cumulative recognition than using any other tested distance measure.

SVM Based Facial Expression Recognition for Expression Control of an Avatar in Real Time (실시간 아바타 표정 제어를 위한 SVM 기반 실시간 얼굴표정 인식)

  • Shin, Ki-Han;Chun, Jun-Chul;Min, Kyong-Pil
    • 한국HCI학회:학술대회논문집
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    • 2007.02a
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    • pp.1057-1062
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    • 2007
  • 얼굴표정 인식은 심리학 연구, 얼굴 애니메이션 합성, 로봇공학, HCI(Human Computer Interaction) 등 다양한 분야에서 중요성이 증가하고 있다. 얼굴표정은 사람의 감정 표현, 관심의 정도와 같은 사회적 상호작용에 있어서 중요한 정보를 제공한다. 얼굴표정 인식은 크게 정지영상을 이용한 방법과 동영상을 이용한 방법으로 나눌 수 있다. 정지영상을 이용할 경우에는 처리량이 적어 속도가 빠르다는 장점이 있지만 얼굴의 변화가 클 경우 매칭, 정합에 의한 인식이 어렵다는 단점이 있다. 동영상을 이용한 얼굴표정 인식 방법은 신경망, Optical Flow, HMM(Hidden Markov Models) 등의 방법을 이용하여 사용자의 표정 변화를 연속적으로 처리할 수 있어 실시간으로 컴퓨터와의 상호작용에 유용하다. 그러나 정지영상에 비해 처리량이 많고 학습이나 데이터베이스 구축을 위한 많은 데이터가 필요하다는 단점이 있다. 본 논문에서 제안하는 실시간 얼굴표정 인식 시스템은 얼굴영역 검출, 얼굴 특징 검출, 얼굴표정 분류, 아바타 제어의 네 가지 과정으로 구성된다. 웹캠을 통하여 입력된 얼굴영상에 대하여 정확한 얼굴영역을 검출하기 위하여 히스토그램 평활화와 참조 화이트(Reference White) 기법을 적용, HT 컬러모델과 PCA(Principle Component Analysis) 변환을 이용하여 얼굴영역을 검출한다. 검출된 얼굴영역에서 얼굴의 기하학적 정보를 이용하여 얼굴의 특징요소의 후보영역을 결정하고 각 특징점들에 대한 템플릿 매칭과 에지를 검출하여 얼굴표정 인식에 필요한 특징을 추출한다. 각각의 검출된 특징점들에 대하여 Optical Flow알고리즘을 적용한 움직임 정보로부터 특징 벡터를 획득한다. 이렇게 획득한 특징 벡터를 SVM(Support Vector Machine)을 이용하여 얼굴표정을 분류하였으며 추출된 얼굴의 특징에 의하여 인식된 얼굴표정을 아바타로 표현하였다.

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Oceanographic indicators for the occurrence of anchovy eggs inferred from generalized additive models

  • Kim, Jin Yeong;Lee, Jae Bong;Suh, Young-Sang
    • Fisheries and Aquatic Sciences
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    • v.23 no.7
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    • pp.19.1-19.14
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    • 2020
  • Three generalized additive models were applied to the distribution of anchovy eggs and oceanographic factors to determine the occurrence of anchovy spawning grounds in Korean waters and to identify the indicators of their occurrence using survey data from the spring and summer of 1985, 1995, and 2002. Binomial and Gaussian types of generalized additive models (GAM) and quantile generalized additive models (QGAM) revealed that egg density was influenced mostly by ocean temperature and salinity in spring, and the vertical structure of temperature, salinity, dissolved oxygen, and zooplankton biomass during summer in the upper quantiles of egg density. The GAM and QGAM model deviance explained 18.5-63.2% of the egg distribution in summer in the East and West Sea. For the principle component analysis-based GAMs, the variance explained by the final regression model was 27.3-67.0%, higher than the regular models and QGAMs for egg density in the East and West Sea. By analyzing the distribution of anchovy eggs off the Korean coast, our results revealed the optimal temperature and salinity conditions, in addition to high production and high vertical mixing, as the key indicators of the major spawning grounds of anchovies.

Detection of Microphytobenthos in the Saemangeum Tidal Flat by Linear Spectral Unmixing Method

  • Lee Yoon-Kyung;Ryu Joo-Hyung;Won Joong-Sun
    • Korean Journal of Remote Sensing
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    • v.21 no.5
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    • pp.405-415
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    • 2005
  • It is difficult to classify tidal flat surface that is composed of a mixture of mud, sand, water and microphytobenthos. We used a Linear Spectral Unmixing (LSU) method for effectively classifying the tidal flat surface characteristics within a pixel. This study aims at 1) detecting algal mat using LSU in the Saemangeum tidal flats, 2) determining a suitable end-member selection method in tidal flats, and 3) find out a habitual characteristics of algal mat. Two types of end-member were built; one is a reference end-member derived from field spectrometer measurements and the other image end-member. A field spectrometer was used to measure spectral reflectance, and a spectral library was accomplished by shape difference of spectra, r.m.s. difference of spectra, continuum removal and Mann-Whitney U-test. Reference end-members were extracted from the spectral library. Image end-members were obtained by applying Principle Component Analysis (PCA) to an image. The LSU method was effective to detect microphytobenthos, and successfully classified the intertidal zone into algal mat, sediment, and water body components. The reference end-member was slightly more effective than the image end-member for the classification. Fine grained upper tidal flat is generally considered as a rich habitat for algal mat. We also identified unusual microphytobenthos that inhabited coarse grained lower tidal flats.

Content Analysis-based Adaptive Filtering in The Compressed Satellite Images (위성영상에서의 적응적 압축잡음 제거 알고리즘)

  • Choi, Tae-Hyeon;Ji, Jeong-Min;Park, Joon-Hoon;Choi, Myung-Jin;Lee, Sang-Keun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.5
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    • pp.84-95
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    • 2011
  • In this paper, we present a deblocking algorithm that removes grid and staircase noises, which are called "blocking artifacts", occurred in the compressed satellite images. Particularly, the given satellite images are compressed with equal quantization coefficients in row according to region complexity, and more complicated regions are compressed more. However, this approach has a problem that relatively less complicated regions within the same row of complicated regions have blocking artifacts. Removing these artifacts with a general deblocking algorithm can blur complex and undesired regions as well. Additionally, the general filter lacks in preserving the curved edges. Therefore, the proposed algorithm presents an adaptive filtering scheme for removing blocking artifacts while preserving the image details including curved edges using the given quantization step size and content analysis. Particularly, WLFPCA (weighted lowpass filter using principle component analysis) is employed to reduce the artifacts around edges. Experimental results showed that the proposed method outperforms SA-DCT in terms of subjective image quality.