• 한국멀티미디어학회논문지
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• 제7권1호
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• pp.27-34
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• 2004

본 논문에서는 컬러 영상에서 색상과 에지 정보를 이용한 얼굴 영역 검출 알고리즘을 제안한다. 제안된 알고리즘은 YCbCr 색공간에서 Cb와 Cr성분을 이용하여 피부색 분할을 한 후에 형태학적 필터링과 레이블링을 통해 얼굴 후보 영역을 분리한다. 분리된 각 후보 영역에 대해 휘도 성분 Y에서 소벨 마스크의 수직 연산자를 적용한 후에 수평 투영을 통해 나타난 최대값을 눈의 위치로 검출해낸다. 비슷하게 얼굴의 지형적인 특징과 소벨 마스크의 수평 연산자를 적용하여 계산된 수평 투영의 최대값에 따라 턱 부분을 검출한다. 실험 결과, 기존의 연구와 검출율을 비슷하면서도 턱의 위치를 검출함으로써 목 부분이 얼굴 영역에 포함되는 것을 방지할 수 있음을 볼 수 있다.

• 한국컴퓨터정보학회논문지
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• 제23권9호
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• pp.1-6
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• 2018

In this paper, we propose a method dividing effectively the hand and fingers using general webcam. The method executes 4 times empirically preprocessing one to erase noise. First, it erases the overall noise of the image using Gaussian smoothing. Second, it changes from RGB image to HSV color model and YCbCr color model, executes a global static binarization based on the statistical value for each color model, and erase the noise through bitwise-OR operation. Third, it executes outline approximation and inner region filling algorithm using RDP algorithm and Flood fill algorithm and erase noise. Lastly, it erases noise through morphological operation and determines the threshold propositional to the image size and selects the hand and fingers area. This paper compares to existing one color based hand area division method and focuses the noise deduction and can be used to a gesture recognition application.

• 한국지반공학회논문집
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• 제28권9호
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• pp.17-22
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• 2012

초대형 사구지역 내 철도공사를 위한 대단위 토공작업을 수행하는 경우, 공사 중 및 공사 후 모래바람에 의한 철도선로의 침식 등으로 인해 철도운행에 큰 지장을 초래할 수 있기 때문에 모래바람에 의한 철도노선 내 모래퇴적 방지공의 계획수립이 매우 중요하다. 효과적인 모래퇴적 방지공을 위해서는 적절한 토공설계뿐만 아니라 펜스 시스템과 같은 직접적 모래바람 억제방법 등에 대한 통합적이고 신중한 고려가 필요하다. 하지만, 현재까지 사용된 여러 방법들을 조사해 본 바에 의하면 모래사막 내 철도건설 시 가장 일반적이고 효과적인 모래퇴적 방지공은 없으며, 모래사막의 사구의 지형학적 연구를 토대로 철도선로 및 모래바람으로부터의 철도선로 보호 구조물 등에 대한 철저한 유지보수 계획의 수립이 더 효과적이고 경제적일 것으로 판단되었다. 본 연구에서는 UAE에서 수행되는 프로젝트 지역 내 사구지역의 대단위 및 특정지역 지형에 대한 조사, 분석을 수행하고, 문헌고찰, 항공사진, 위성사진, 현장조사 등을 통해 프로젝트 지역 내 사구의 이동경로, 이동속도를 추정하여 모래바람에 의한 철도선로 침식방지 구조물의 설계 및 유지 보수 계획 수립에 기여하는 것에 그 목적을 두었다.

• 펄프종이기술
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• 제38권4호
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• pp.17-23
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• 2006

Paper has fibers and fines network structure and it is strongly affected by interface bond-ing between fibers. Paper structural properties can be determined depending on the inter-fiber bonding. Fines play an important role in Campbell and consolidation effect through wet pressing and drying operations. The fines are essential for the formation of bonds between fibers and for the improvement of strength properties of papers. Since the fines are components of the pulp, there are always two factors to be considered: the quality and quantity of the fines. The quality of fines might be a potential variable to give a more accurate picture of the papermaking potential of the pulp. The object of this study is to investigate the effect of different types of pulp fines on the properties of paper and to access the potential of fines for controlling the bulk of paper. Refined Sw-BKP, Hw-BKP and BCTMP fines were used to investigate the fines effect. Wet-web strength, breaking length, scattering coefficient, and hydrodynamic specific volume, and drying shrinkage were measured. According to the results, chemical and morphological compositions of fines do not strongly affect to wet-web forming by their similar Campbell effect, but strongly affect to drying operation which forms hydrogen bonding among fiber-fines-fiber matrixes. Paper bulk should be controlled by the extent of hydrogen bonding between fibers during drying operation.

• 한국정밀공학회지
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• 제16권12호
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• pp.60-70
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• 1999

An efficient automatic inspection system for Floating Seal is developed, The proposed system consists of a high resolution line scan camera, microcomputer, and PLC (Programmable Logic Controller). In order to perform rapid inspection, The ROI (Region of Interest) is extracted from the original image. There are types of defects; shape defects and surface defects. Each features of defects are captured by edge detect, segmentation, morphological operation, and threshold analysis. PLC controller is used to synchronize the whole system and store the inspection results temporarily to reduce the overhead of microcomputer. As a result, the system is being utilized successfully in a teal inspection line.

• Journal of Computing Science and Engineering
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• 제8권3호
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• pp.149-156
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• 2014

Skeletonization is a morphological operation that transforms an original object into a subset, which is called a 'skeleton'. Skeletonization has been intensively studied for decades and is a challenging issue especially for special target objects. This paper proposes a novel approach to the skeletonization of text images based on stroke width detection. First, the preliminary skeleton is detected by using a Canny edge detector with a Tensor Voting framework. Second, the preliminary skeleton is smoothed, and junction points are connected by interpolation compensation. Experimental results show the validity of the proposed approach.

• Journal of information and communication convergence engineering
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• 제6권2호
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• pp.204-206
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• 2008

In this paper, we proposed the recognition method that automatically extracts cracks from a surface image acquired by a digital camera and recognizes the directions (horizontal, vertical, -45 degree, and 45 degree) of cracks using the fuzzy single layer perceptron. We compensate an effect of light on a concrete surface image by applying the closing operation, which is one of the morphological techniques, extract the edges of cracks by Sobel masking, and binarize the image by applying the iterated binarization technique. Two times of noise reduction are applied to the binary image for effective noise elimination. After the specific regions of cracks are automatically extracted from the preprocessed image by applying Glassfire labeling algorithm to the extracted crack image, the cracks of the specific region are enlarged or reduced to $30{\times}30$ pixels and then used as input patterns to the fuzzy single layer perceptron. The experiments using concrete crack images showed that the cracks in the concrete crack images were effectively extracted and the fuzzy single layer perceptron was effective in the recognition of the extracted cracks directions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.60-62
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• 2005

In this study, the automatic tracking algorithm tracing a human face is proposed by using YCbCr color coordinated information and its thermal properties expressed in terms of thermal indexes in an infra-red image. The facial candidates are separately estimated in CbCr color and infra-red domain, respectively with applying the morphological image processing operations and the geometrical shape measures for fitting the elliptical features of a human face. The identification of a true face is accomplished by logical 'AND' operation between the refined image in CbCr color and infra-red domain.

• 한국식물병리학회지
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• 제10권2호
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• pp.99-104
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• 1994

A computer-based diagnosing system for diseases of grasses, ornamental plant and fruit trees was developed using a 16 bit personal computer (Model Acer 900) and BASIC was used as a programing language. the developed advisory system was named as Korean Plant Disease Advisory System (KOPDAS). The diagraming system files were composed of a system operation file and several database files. The knowledge-base files are composed of text files, code files and implement program files. The knowledge-base of text files are composed of 79 files of grasses diseases, 122 files of ornamental plant diseases and 67 files of fruit tree diseases. The information of each text file include disease names, causal agents, diseased parts, symptoms, morphological characteristics of causal organisms and control methods for the diagnosing of crop diseases.

• 제어로봇시스템학회논문지
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• 제22권4호
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• pp.288-292
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• 2016

In this paper, we propose an infrared image based human victim recognition method for a search and rescue robot in dark environments, like general disaster situations. For recognizing a human victim, an infrared camera on a RGB-D camera, Microsoft Kinect, is used. The contrast and brightness of the infrared image are first improved by histogram equalization, and the noise on the image is removed by morphological operation and Gaussian filtering. For recognizing a human victim, the binarization and blob labeling methods are applied to the improved image. Finally, for verifying the effectiveness and feasibility of the proposed method, an experiment for human victim recognition is carried out in a dark environment.