• 한국의상디자인학회지
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• 제16권4호
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• pp.189-203
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• 2014

In this study, Creative motifs using face composition of Jogakbo and Knot Symbol were developed, and applied to traditional Baeja of Joseon Dynasty to develop design contents of traditional clothes. As for study method, 7 motifs of new formative image that integrates traditional beauty and contemporary sense were developed by applying Knot Symbols and face compositions of Jogakbo with the use of Adobe Illustrator CS6 and Adobe Photoshop CS6 vector graphic software. The motifs were designed in contemporary image in face compositions like rectangle pattern, triangle pattern, dual rectangle pattern, vertical and horizontal pattern, pinwheel pattern, gojunmun pattern and free pattern by involving various changes like repetition, rotation, reduction, expansion and decomposition and using the colors used in the Jogakbo. It is desired that through this study, traditional Baeja may develop to bear traditional and contemporary image so that our traditional clothes design may become global. Also it is anticipated that this study will contribute to development of culture products of Hanbok like Jeogori, pants and skirt that require change of design in the global era while maintaining traditional beauty to appeal to the emotions of world citizens.

• Journal of Biosystems Engineering
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• 제27권2호
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• pp.151-160
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• 2002

Cow image processing technique would be useful not only for recognizing an individual but also for establishing the image database and analyzing the shape of cows. A cow (Holstein) has usually the unique speckle pattern. In this study, the individual recognition of cow was carried out using the speckle pattern and the content-based image retrieval technique. Sixty cow images of 16 heads were captured under outdoor illumination, which were complicated images due to shadow, obstacles and walking posture of cow. Sixteen images were selected as the reference image for each cow and 44 query images were used for evaluating the efficiency of individual recognition by matching to each reference image. Run-lengths and positions of runs across speckle area were calculated from 40 horizontal line profiles for ROI (region of interest) in a cow body image after 3 passes of 5$\times$5 median filtering. A similarity measure for recognizing cow individuals was calculated using Euclidean distance of normalized G-frame histogram (GH). normalized speckle run-length (BRL), normalized x and y positions (BRX, BRY) of speckle runs. This study evaluated the efficiency of individual recognition of cow using Recall(Success rate) and AVRR(Average rank of relevant images). Success rate of individual recognition was 100% when GH, BRL, BRX and BRY were used as image query indices. It was concluded that the histogram as global property and the information of speckle runs as local properties were good image features for individual recognition and the developed system of individual recognition was reliable.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.789-792
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• 2003

Pipe inspection has a great importance to ensure safety for the nuclear power plant. In this paper, we designed visual inspection module for the tube internal, which diameter is 15${\sim}$20mm. And we made inspection module which consisted of CCD camera and light. And the relation between image and real world coordinate is established. Image processing is performed to calculate mapping parameter and analyze the size of defect. For the calculation of mapping parameter, experiment is performed using grid type test pattern. Acquired image is processed to extract image coordinate. Edge detection, thresholding, median filtering and morphology filtering is applied to extract grid pattern. Extracted image coordinate is used to calculate image to real world mapping. Lens distortion was considered and corrected to get exact data. Coordinate transformation data is provided for the users to recognize easily. Experiment was performed using grid type test pattern, we extracted lens distortion parameter and real coordinate of defect point. Radial distortion of lens was corrected but tangential distortion was not considered. As continuum to this study, the tangential distortion of lens is considered and improvement of analy zing technique for the tube internal be explored continuously.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.261-263
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• 2005

In this paper, we implement an identification system using the vein image of the hand. The vein pattern is obtained in the grey-scale 2D image through the infrared-red imaging from back of the hand. Since the frame has lack of clearance, we use some enhancing methods such as the complement, addition, and multiplication to the image to increase the contrast. After Wiener filtering for smoothness of the vein pattern, we transform the image into the binary image with mean function. The binarized image is session thinned and the cross-points in the vein tree are obtained by calculating the number of pixels connected because the image is shaped as a tree. We choose the point and find the nearest to the center if it has majority, where we find the two end points of the selected line. We can get the angle between the two lines joined at the cross-point and store its coordinates, angle, and label the values. The values are used as the feature vector of the vein pattern. This procedure is similar to the human cognition sequences. It is shown that the proposed method is simple for the vein recognition.

• Smart Structures and Systems
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• 제17권6호
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• 한국정보통신학회논문지
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• 제19권4호
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• pp.940-947
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• 2015

본 논문에서는 기존의 터치 센서방법과 초음파나 레이저를 사용하는 방법이 아닌 디스플레이에 프린트된 매트릭스 패턴 영상을 이용하여 위치 정보를 추출하는 시스템의 패턴 영상의 특징점을 찾고 관심 영역의 영상을 추출하는 방법을 제안하였다. 제안하는 방법은 패턴 영상의 조도값과 패턴의 특징을 이용하여 촬영된 영상의 회전된 각도와 신뢰성 있는 특징점을 찾고 관심영역을 추출한다. 성공적인 관심 영역 추출을 위해서 다양한 각도에서 판서된 패턴영상을 이용하여 위치 관심영역 추출을 테스트하였고 성공적으로 관심영역을 추출하는 것을 확인하였다. 제안한 알고리즘은 OpenCV와 Window 프로그램을 사용하여 소프트웨어적으로 검증하고, 또한, Verilog-HDL을 사용하여 하드웨어 시스템을 설계하고, Xilinx FPGA(xc6vlx760) 보드를 이용하여 검증하였다.

• Journal of Biosystems Engineering
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• 제38권1호
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• pp.55-63
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• 2013

Purpose: The present study aimed at image processing methods for automatic cell pattern recognition and morphological analysis for tissue engineering applications. The primary aim was to ascertain the novel algorithm of adaptive brightness correction from microscopic images for use as a potential image analysis. Methods: General microscopic image of cells has a minor problem which the central area is brighter than edge-area because of the light source. This may affect serious problems to threshold process for cell-number counting or cell pattern recognition. In order to compensate the problem, we processed to find the central point of brightness and give less weight-value as the distance to centroid. Results: The results presented that microscopic images through the brightness correction were performed clearer than those without brightness compensation. And the classification of mixed cells was performed as well, which is expected to be completed with pattern recognition later. Beside each detection ratio of hBMSCs and HeLa cells was 95% and 92%, respectively. Conclusions: Using this novel algorithm of adaptive brightness correction could control the easier approach to cell pattern recognition and counting cell numbers.

• 정보보호학회논문지
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• 제9권4호
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• pp.37-48
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• 1999

현대암호방식은 종래의 선형 대수와 수리이론을 적용한 암호통신을 벗어난 유사 잡음성을 띠는 카오스 신호를 이용한 암호통신을 적용해 오고 있다,[1-2] 본 논문은 1차 permutation 알고 리즘을 이용 하여 변환된 정보를 2차 이산 카오스 변환 함수를 이용해 암호화하는 광영상 암호시스템을 제안하여UT 다. 제안된 시스템은 키수열 발생기의 출력을 통해 영상정보를 permutation 하는 알고리즘 을 설계하였고 이에 대한 검정을 수행하였다. 또한 본 논문에서는 permutation 알고리즘을 통해 제한적인 카오스 함수 의 적용시 발생하는 문제점을 해결하고 비도를 증가시킴으로써 광영상 암호시스템에 적용 시 그 타당성 을 검정하였다. Current encryption methods have been applied to secure communication using discrete chaotic system whose output is a noise-like signal which differs from the conventional encryption methods that employ algebra and number theory[1-2] We propose an optical encryption method that transforms the primary pattern into the image pattern of discrete chaotic function first a primary pattern is encoded using permutation algorithm, In the proposed system we suggest the permutation algorithm using the output of key steam generator and its security level is analyzed. In this paper we worked out problem of the application about few discrete chaos function through a permutation algorithm and enhanced the security level. Experimental results with image signal demonstrate the proper of the implemented optical encryption system.

• 한국인터넷방송통신학회논문지
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• 제12권3호
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• pp.29-35
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• 2012

본 논문에서는 MPEG(Moving Picture Experts Group) 영상 디코더에서 영상을 압축, 비교, 복원, 저장한후 디코딩 처리하는 방법을 종래의 픽셀 단위로 처리하는 방법과는 다르게 영상의 단위 화소 주변을 군집화소로 분류한 후 이를 클러스터링하여 오버랩정도를 결정 한다. 오버랩 정도의 임계치값을 결정하는데는 패턴식별을 취한후 샘플 패턴에 대한 기하구조의 파악과 결정함수의 도출로 활용된다. 특징공간이 4차원 이상이면 주어진 패턴 구조를 시각적으로 관찰할 수 없다. 이 때, 분포구조를 고찰해 볼수 있는 방법은 군집중심간의 거리, 군집별 패턴의 수 및 표준편차 등을 이용하는 방법이다. 임계치 값을 넘는 중복화면은 소거되고 넘지않는 군집화면은 패턴인식으로 복원된후 동영상으로 구현된다. 이방법이 기존의 픽셀 단위 처리하는 방법 과는 20%정도의 메모리 감축과 15%정도의 화면 복원에 성능이 향상된 것으로 판정된다.

• 한국지능시스템학회논문지
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• 제13권2호
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• pp.154-162
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• 2003

셀룰라 신경회로망의 연상 메모리를 이용하여 시각적인 입력 데이터의 연산을 통하여 영상 패턴의 분류와 인식을 수행한다. 셀룰라 신경회로망은 일반적인 신경회로망과 같이 비선형 데이터의 실시간 처리가 가능하고, 세포자동자와 같이 이 격자구조의 셀로 이루어져 인접한 셀과 직접 정보를 주고받는다. 응용 분야로는 최적화, 선형/비선형화, 연상 메모리, 패턴인식, 컴퓨터 비전 등에 적용할 수 있다. 영상의 이미지 픽셀을 셀룰라 신경회로망의 셀에 대응하여 전체 이미지 영상을 모든 셀룰라 신경회로망의 셀에서 동시에 병렬로 처리할 수 있어 2-D 이미지 처리에 적합하다. 본 논문은 셀룰라 신경회로망에 의한 연상 메모리 구조를 설계하고, 학습된 하중값 메모리에서 가장 적당한 하중값을 선택하여 학습된 영상과 정확히 일치하는 출력을 얻는 방법을 제시한다. 학습을 통한 연상 메모리 구현에는 각각의 뉴런에서 일정하지 않은 다른 템플릿을 사용한다. 각각의 템플릿은 뉴런들 간의 연결 하중값을 나타내고 학습에 따라 갱신된다. 학습방법으로는 템플릿 하중값 학습에 뉴런들 간의 연결 하중값을 조정하는 가장 단순한 규칙인 Hebb의 학습방법이 사용되었고 분류값 학습에 LMS 알고리즘이 사용되었다.