• 제어로봇시스템학회논문지
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• 제11권2호
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• pp.137-143
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• 2005

Autonomous mobile robot has an ability to navigate using both map in known environment and sensors for detecting obstacles in unknown environment. In general, autonomous mobile robot navigates by global path planning on the basis of already made map and local path planning on the basis of various kinds of sensors to avoid abrupt obstacles. This paper provides a global path planning method using self-organizing feature map which is a method among a number of neural network. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.301-304
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• 2008

Since longer wavelength microwave radiation can penetrate clouds, satellite passive microwave sensors can observe sea ice of the entire polar region on a daily basis. Thus, it is becoming popular to derive sea ice motion vectors from a pair of satellite passive microwave sensor images observed at one or few day interval. Usually, the accuracies of derived vectors are validated by comparing with the position data of drifting buoys. However, the number of buoys for validation is always quite limited compared to a large number of vectors derived from satellite images. In this study, the sea ice motion vectors automatically derived from pairs of AMSR-E 89GHz images (IFOV = 3.5 ${\times}$ 5.9km) by an image-to-image cross correlation were validated by comparing with sea ice motion vectors manually derived from pairs of cloudless MODIS images (IFOV=250 ${\times}$ 250m). Since AMSR-E and MODIS are both on the same Aqua satellite of NASA, the observation time of both sensors are the same. The relative errors of AMSR-E vectors against MODIS vectors were calculated. The accuracy validation has been conducted for 5 scenes. If we accept relative error of less than 30% as correct vectors, 75% to 92% of AMSR-E vectors derived from one scene were correct. On the other hand, the percentage of correct sea ice vectors derived from a pair of SSM/I 85GHz images (IFOV = 15 ${\times}$ 13km) observed nearly simultaneously with one of the AMSR-E images was 46%. The difference of the accuracy between AMSR-E and SSM/I is reflecting the difference of IFOV. The accuracies of H and V polarization were different from scene to scene, which may reflect the difference of sea ice distributions and their snow cover of each scene.

• 전기학회논문지
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• 제58권12호
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• pp.2511-2519
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• 2009

In this paper, we introduce the methodological system design via feature selection using Principal Component Analysis and Particle Swarm Optimization algorithms. The overall methodological system design comes from three kinds of modules such as preprocessing module, feature extraction module, and recognition module. First, Histogram equalization enhance the quality of image by exploiting contrast effect based on the normalized function generated from histogram distribution values of 2D face image. Secondly, PCA extracts feature vectors to be used for face recognition by using eigenvalues and eigenvectors obtained from covariance matrix. Finally the feature selection for face recognition among the entire feature vectors is considered by means of the Particle Swarm Optimization. The optimized Polynomial-based Radial Basis Function Neural Networks are used to evaluate the face recognition performance. This study shows that the proposed methodological system design is effective to the analysis of preferred face recognition.

• 한국정보통신학회논문지
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• 제23권6호
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• pp.682-689
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• 2019

부분 기반 영상 표현(part-based image representation)에서는 영상의 부분적인 모습을 기저 벡터로 표현하고 기저 벡터의 선형 조합으로 영상을 분해하며, 이 때 기저 벡터의 계수가 곧 물체의 부분적인 특징을 의미하게 된다. 본 논문에는 부분 기반 영상 표현 기법인 비음수 행렬 분해(non-negative matrix factorization, NMF)를 이용하여 얼굴 영상을 표현하고 신경망 기법을 적용하여 가려진 얼굴을 인식하는 얼굴 인식을 제안한다. 표준 비음수 행렬 분해, 투영 경사 비음수 행렬 분해, 직교 비음수 행렬 분해를 이용하여 얼굴 영상을 표현하였고, 각 기법의 성능을 비교하였다. 인식기로는 학습벡터양자화 신경망을 사용하였으며, 인식기에서의 거리 척도로는 유클리디언 거리를 사용하였다. 실험 결과, 전통적인 얼굴 인식 방법에 비하여 제안한 기법이 가려진 얼굴 인식에 보다 강인함을 보인다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.11-14
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• 1996

Performance of the group cumulative sum(CUSUM) control scheme using multiple univariate CUSUM charts is more sensitive to the change of quality control(QC) characteristics than the control chart scheme based on the Hotelling statistics. We examine three group charts for multivariate normal data sets simulated with various correlation structures and shift directions in the mean vector. These group schemes apply the orginal measurement vectors, the scaled residual vectors from the regression of each variable on all others and the principal component vectors respectively to calculating the CUSUM statistics. They are also compared to the multivariate QC charts based on the Hotelling statistic by estimating average run lengths, coefficients of variation of run length and ranks in signaling order. On the basis of simulation results, we suggest a control chart scheme appropriate for specific quality control environment.

• Management Science and Financial Engineering
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• 제5권1호
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• pp.51-71
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• 1999

Performance of the group cumulative sum (CUSUM) control scheme using multiple univariate CUSUM charts is more sensitive to the change of quality control (QC) characteristics than the control chart schemes based on the Hotelling statistic We vexamine three group charts for multivariate normal data sets simulated with various correlation structures and shift directions in the mean vector. These group schemes apply the original measurement vectors, the scaled residual vectors from the re-gression of each variable on all others and the principal component vectors respectively to calculat-ing the CUSUM statistics. They are also compared to the multivariate QC charts based on the Ho-telling statistic by estimating average run lengths, coefficients of variation of run length and ranks in signaling order. On the basis of simulation results, we suggest a control chart scheme appropriate for specific quality control environment.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1999년도 KOBA 방송기술 워크샵 KOBA Broadcasting Technology Workshop
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• pp.69-76
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• 1999

This paper proposes a new region-oriented coding scheme of still images. The scheme first segments an image into homogeneous regions by making use of Voronoi diagrams. Then luminance components in each Voronoi region are encoded using a transform coding technique which employs the Schmidt's orthogonalization method to produce orthonormal basis-functions for arbitrarily shaped regions. In this technique, coding efficiency depends on the properties of initial vectors to be orthogonalized. Therefore we adaptively select a set of initial vectors as well as the order in which these vectors are orthogonalized. Simulation results indicate that the proposed coding scheme achieves higher coding performance with much less computation than the KLT-based scheme which we reported formerly.

• Parasites, Hosts and Diseases
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• 제55권5호
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• pp.579-582
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• 2017

To investigate the prevalence of intestinal parasite infections in Yanbian Prefecture, Jilin Province, China, epidemiological surveys were conducted on a collaboration basis between the Korean Centers for Disease Control and Prevention and the Yanbian Center for Disease Control and Prevention. A total of 8,396 (males 3,737 and females 4,659) stool samples were collected from 8 localities and examined with the formalin-ether sedimentation technique, and additionally examined with the cellotape anal swab to detect Enterobius vermicularis eggs. The overall rate of intestinal parasites was 1.57%. The prevalence of Ascaris lumbricoides was the highest (0.80%), followed by Entamoeba spp. (0.23%), heterophyid flukes (0.15%), Clonorchis sinensis (0.08%), Enterobius vermicularis (0.07%), hookworms (0.06%), Trichostrongylus spp. (0.06%), Giardia lamblia (0.04%), Paragonimus spp. (0.02%), Diphyllobothrium spp. (0.02%), Trichuris trichiura (0.02%). The prevalence by sex was similar, 1.58% (n=59) in males and 1.57% (n=73) in females. By the present study, it is partly revealed that the prevalences of intestinal parasite infections are relatively low among the inhabitants of Yanbian Prefecture, Jilin Province, China.

• 방송공학회논문지
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• 제17권1호
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• pp.195-198
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• 2012

일반적으로 표면반사율과 분광반사율을 N차원의 칼라 코드로부터 정확히 복원하기 위해서는 N개의 기저함수가 필요하다. 전형적인 렌더링 응용에서 벡터의 덧셈, 스칼라 곱셈 및 성분별 곱셈에 대한 벡터 연산이 이질동형이라고 가정하고 광원의 중첩, 광원-표면간 상호간섭 및 상호반사와 같은 물리적인 연산을 모델링하지만 벡터 연산이 물리적인 현상을 그대로 반영하는 것은 아니다. 그러나 만약 기저함수가 특성함수로써 제한된다면 표면반사율과 분광반사율의 사상 결과 및 벡터들은 렌더링에서 물리적인 연산인 이질이형을 유지하게 된다. 본 논문은 새로운 N차원의 특성함수를 제안하고 N차원의 기저함수로 근사화된 먼셀 칼라 칩에 대하여 제안한 알고리즘의 정확성을 평가할 것이다.

• 전자공학회논문지
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• 제54권3호
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• pp.55-62
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• 2017

비음수 행렬 분해 기법(non-negative matrix factorization)은 대표적인 부분 영역 기반 표현 기법의 하나로 영상의 부분적인 특징을 나타내는 기저 벡터의 선형 조합으로 영상을 표현하는 기법이다. 본 논문에서는 여러 가지 비음수 행렬 분해 기법을 이용하여 얼굴 영상을 표현하고, 추출된 특징을 기반으로 학습 벡터 양자화를 이용하여 얼굴 인식을 수행하였다. 추출된 각 기법의 기저 벡터를 비교하여 각 기법의 특징을 분석하였다. 또한 NMF 기법들의 인식율 검증을 통해 비음수 행렬 기법의 얼굴 인식에 대한 활용 가능성을 확인하였다.