• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.171.5-171
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• 2001

Information that is acquired by adhered sensors on a body has been commonly used for the three-dimensional real-time motion capture algorithm. This paper describes realtime motion capture algorithm using computer vision. In a real-time image sequence, human body silhouette is extracted use a background subtraction between background image and the reference image. Then a human standing posture whether forward or backward is estimated by extraction of skin region in the silhoutte. After then, the principal axis is calculated in the torso and the face region is estimated on the principal axis. Feature points, which are essential condition to track the human gesture, are obtained ...

• 한국정밀공학회지
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• 제13권3호
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• pp.102-109
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• 1996

In this paper, we present a new approach for the automation of deburring process. An algorithm for teaching skills of a human expert to a robot manipulator is developed. This approach makes use of TSK fuzzy mode that can wxpress a highly nonlinear functional relation with small number of rules. Burr features such as height, width, area, grinding area are extracted from image processing by use of the vision system. Grinding depth, repetitive number and normal grinding force are chosen as control signals representing actions of the human expert. It is verified that our proposed fuzzy model can accurately express the skills of human experts for the deburring process.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.1243-1253
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• 1993

Visual features of a mushroom(Lentinus Edodes L) are critical in sorting and grading as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. Though actions involved in human grading looks simple, a decision making undereath the simple action comes form the results of the complex neural processing of the visual image. And processing details involved in the visual recognition of the human brain has not been fully investigated yet. Recently, however, an artificial neural network has drawn a great attention because of its functional capability as a partial substitute of the human brain. Since most agricultural products are not uniquely defined in its physical properties and do not have a well defined job structure, a research of the neuro-net based human like information processing toward the agricultural product and processing are widely open and promising. In this pape , neuro-net based grading and sorting system was developed for a mushroom . A computer vision system was utilized for extracting and quantifying the qualitative visual features of sampled mushrooms. The extracted visual features and their corresponding grades were used as input/output pairs for training the neural network and the trained results of the network were presented . The computer vision system used is composed of the IBM PC compatible 386DX, ITEX PFG frame grabber, B/W CCD camera , VGA color graphic monitor , and image output RGB monitor.

• 대한한의학회지
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• 제27권1호
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• pp.57-77
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• 2006

Objectives : The purpose of this study is to review research papers published by Korean research groups on biophoton of human beings based on experiment subject and methodology. Methods : In order to review human biophoton research executed in Korea, all the papers published in Korean and international journals by Korean research groups were selected. Several key foreign papers were also reviewed for clarification of this study. Based on experiment subjects, experiment methodology, and interpretation of experiment results were analyzed. On each experiment, its original interpretation was directly quoted. Issues on the experiment methodology and interpretation were expressed at the end of each subject. Results and Conclusions : We found that experiments on human biophoton were compelling. However it seemed that more experiments, especially on their sample sizes, are needed to demonstrate its clinical application. Interpretations based on Korean traditional medicine also need to be elaborated more. In order to do accomplish clinical application of biophoton, interdisciplinary works are required. Some suggestions on biophoton experiments were made.

• 전자공학회논문지SC
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• 제46권4호
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• pp.58-63
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• 2009

각종 전자 제품 및 부품의 외관 검사는 인간의 시력에 의해 이루어졌다. 외관 검사는 LCD Panel, flexible PCB 및 다른 여러 가지 전자부품에 적용되어진다. 전자 제품의 외관검사를 사람의 시력에 의존할 경우 작고 미세한 전자 제품은 검사자의 신체와 정신에 따라 검사 결과가 변화하기 때문에 안정적인 결과를 기대 할 수 없다. 머신비전 시스템은 이러한 문제가 발생되지 않는다. 따라서 머신 비전 시스템은 현제 여러 외관 검사 분야에서 사용되어지고 있다. 하지만 머신 비전 시스템에 의한 자동 검사는 작업장의 조명에 의한 영향을 많이 받는다. 본 논문에서는 이러한 영향을 극복하기 위한 방법으로 히스토그램변환을 이용한 머신비전 검사의 정확성 향상 방법을 제안한다.

• 한국지능시스템학회논문지
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• 제26권1호
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• pp.70-75
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• 2016

머신비전을 사용하여 사람의 얼굴을 인식하는 다양한 연구가 진행되고 있다. 머신비전은 기계에 시각을 부여하여 이미지를 분류 혹은 분석하는 기술을 의미한다. 본 논문에서는 이러한 머신비전 기술을 적용한 얼굴을 분류하는 알고리즘을 제안한다. 이 얼굴 분류 알고리즘을 구현하기 위해 컨볼루셔널 신경망(Convolution neural network)과 Cascade 안면 검출기를 사용하였고, 피험자들의 얼굴을 분류하였다. 구현한 얼굴 분류 알고리즘의 학습을 위해 한 피험자 당 이미지 2,000장, 3,000장, 40,00장을 10회와 20회 컨볼루셔널 신경망에 각각 반복하여 학습과 분류를 진행하였고, 학습된 컨볼루셔널 신경망과 얼굴 분류 알고리즘의 실효성을 테스트하기 위해 약 6,000장의 이미지를 분류하였다. 또한 USB 카메라 영상을 실험 데이터로 입력받아 실시간으로 얼굴을 검출하고 분류하는 시스템을 구현하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1126-1129
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• 2003

In this paper, we propose a multi-agent system for assisting those who need help in taking objects around him/her. One may imagine this kind of situation when a person is lying in bed and wishes to take an object on a distant table that cannot be reached only by stretching his/her hand. The proposed multi-agent system is composed of three main independent agents; a vision agent, a robot agent, and a pass agent. Once a human expresses his/her intention by pointing to a particular object using his/her hand and a finger, these agents cooperatively bring the object to him/her. Natural communication between a human and the multi-agent system is realized in this way. Performance of the proposed system is demonstrated in an experiment, in which a human intends to take one of the four objects on the floor and the three agents successfully cooperate to find out the object and to bring it to the human.

• 품질경영학회지
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• 제44권3호
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• pp.527-540
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• 2016

Purpose: The purpose of this study was to propose contrast metric which is based on the human visual perception and thus it can be used to improve the quality of digital images in many applications. Methods: Previous literatures are surveyed, and then the proposed method is modeled based on Human Visual System(HVS) such as multiscale property of the contrast sensitivity function (CSF), contrast constancy property (suprathreshold), color channel property. Furthermore, experiments using digital images are shown to prove the effectiveness of the method. Results: The results of this study are as follows; regarding the proposed contrast measure of complex images, it was found by experiments that HVS follows relatively well compared to the previous contrast measurement. Conclusion: This study shows the effectiveness on how to measure the contrast of complex images which follows human perception better than other methods.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.313-316
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• 2015

Construction is one of the most dangerous job sectors, which reports tens of thousands of time-loss injuries and deaths every year. These disasters incur delays and additional costs to the projects. The safety management needs to be on the top primary tasks throughout the construction to avoid fatal accidents and to foster safe working environments. One of the safety regulations that are frequently violated is the wearing of personal protection equipment (PPE). In order to facilitate monitoring of the compliance of the PPE wearing regulations, this paper proposes a vision based method that automatically identifies whether workers wear hard hats and safety vests. The method involves three modules - human body detection, identification of safety vest wearing, and hard hat detection. First, human bodies are detected in the video frames captured by real-time on-site construction cameras. The detected human bodies are classified into with/without wearing safety vests based on the color features of their upper parts. Finally, hard hats are detected on the nearby regions of the detected human bodies and the locations of the detected hard hats and human bodies are correlated to reveal their corresponding matches. In this way, the proposed method provides any appearance of the workers without wearing hard hats or safety vests. The method has been tested on onsite videos and the results signify its potential to facilitate site safety monitoring.

• 한국산학기술학회논문지
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• 제11권5호
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• pp.1558-1563
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• 2010

본 논문에서는 생산 현장에서 작업자가 육안으로 하고 있는 자동차 부품의 전수(全數) 검사 방법을 대체하기 위한 머신 비전 시스템의 개발을 위한 검사알고리즘에 관한 연구이다. 생산 효율과 품질 향상을 위한 노력의 일환으로 플라스틱 압출 성형에서 생기는 여러 가지 불량품 유형을 PC를 기반한 머신 비전 시스템(Machine Vision System)을 구축하기에 앞서 생산된 부품을 실시간 검사하고 제품의 불량 유무를 판별하는 알고리즘을 개발하는 것이 본 연구의 목적이다. 검사방법에 사용된 소프트웨어는 NI-LabVIEW를 사용하였으며, LabVIEW Vision 이미지 함수를 사용하여 검사 프로그램을 개발하였다. 개발된 검사 알고리즘은 생산 부품의 실시간 검사에 적용 될 수 있으며, 검사 영역과 설정 값을 비전 시스템 운용자가 설정할 수 있도록 프로그램이 만들어져 검증되었다.