• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1999.07a
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• pp.142-149
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• 1999

최근 주변첨단기술이 발달하여 수확, 접목 및 착유 등 농작업에 로봇을 응용하기 위한 연구가 수행되고 있다. 작업의 특성에 따라 응용되는 로봇기술도 차이는 있겠으나 수확용 로봇의 경우 대상물을 인식하고 위치를 검출하는 기술개발이 선행되어야만 대상물을 파지 또는 절단하여 수확이 가능하며, 대상물의 인식 및 위치 검출에는 영상처리기술이 많이 응용되고 있다. 따라서 수확로봇의 작업성능은 대상물을 얼마나 정확하게 인식하고 위치를 정확하게 검출하는 것이 중요하다. 그러나 작업대상이 일정한 조건에서 표준화 되어있는 일반 산업분야와는 달리 농산물의 수확작업현장은 대상물의 배치, 크기 및 형상 둥이 일정하지 않고 작업환경 또한 다양하여 외란의 영향을 많기 받기 때문에 시각장치의 개발은 매우 중요하다. (중략)

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1035-1045
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• 2004

In this paper, we describe a method that can recognize gestures and evaluate the degree of the gestures from sequential gesture images by using Gesture Feature Space. The previous popular methods based on HMM and neural network have difficulties in recognizing the degree of gesture even though it can classify gesture into some kinds. However, our proposed method can recognize not only posture but also the degree information of the gestures, such as speed and magnitude by calculating distance among the position vectors substituting input and model images in parametric eigenspace. This method which can be applied in various applications such as intelligent interface systems and surveillance systems is a simple and robust recognition algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.3
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• pp.118-123
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• 1999

Hough transform is well employed to retect or recognize the lines in image processing or in computer vision. Curve of the logarithm of ranges against the bearing does not change its shape according to data trints. This fact suggests that calculation cost can be remarkably reduced. An effective line detection algorithm is represented.sented.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.553-555
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• 2003

사람의 얼굴을 검출 및 인식을 하는 여러 가지 다양한 알고리즘이 소개되고 있다. 본 논문에서는 사람의 피부색을 이용한 컬러정보(Color Information)와 국부 최적 임계치 기법을 사용하여 얼굴의 형상정보를 검출하고 얼굴 영역을 검출하는 방법을 사용한다. 컬러정보를 사용하여 얼굴의 후보영역을 선정한 후에 그 후보영역에서 얼굴의 특징인 눈, 눈썹, 입을 찾는 방법을 제안한다. 피부색은 일정한 분포를 가지고 있기 때문에 후보영역을 비교적 정확히 찾을 수 있으며, 국부 최적 임계치 기법은 효과적인 얼굴 특징 검출방법이다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.353-354
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• 2009

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.280-285
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• 2004

In this study, we made a comparative study of backpropagation neural network and probabilistic neural network and bayesian classifier and perceptron as shape recognition algorithm of welding flaws. For this purpose, variables are applied the same to four algorithms. Here, feature variable is composed of time domain signal itself and frequency domain signal itself. Through this process, we comfirmed advantages/disadvantages of four algorithms and identified application methods of four algorithms.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.2
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• pp.169-176
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• 2013

To generate the walking path of a humanoid robot in an unknown environment, the shapes of obstacles around the robot should be detected accurately. However, doing so incurs a very large computational cost. Therefore this study proposes a method to classify the obstacle shape into three types: a shape small enough for the robot to go over, a shape planar enough for the robot foot to make contact with, and an uncertain shape that must be avoided by the robot. To classify the obstacle shape, first, the range and the number of the obstacles is detected. If an obstacle can make contact with the robot foot, the shape of an obstacle is accurately derived. If an obstacle has uncertain shape or small size, the shape of an obstacle is not detected to minimize the computational load. Experimental results show that the proposed algorithm efficiently classifies the shapes of obstacles around the robot in real time with low computational load.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.182-189
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• 2014

This paper proposed a framework of recognition and tracking for underwater objects using sonar images as an alternative of underwater optical camera which has the limitation of usage due to turbidity. In Part 1, a design and recognition method for 2D artificial landmark was proposed considering the practical performance of current imaging sonars. In particular, its materials are selected in order to maximize detectability based on characteristics of imaging sonar and ultrasonic waves. It has a simple and omni-directional shape which allows an easy modeling of object, and it includes region based features as identifications. Also, we proposed a real-time recognition algorithm including edge detector, Hough circle transforms, and shape matrix based recognition algorithm. The proposed methods are verified by basin tests using DIDSON.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.474-483
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• 2004

In this paper, we present a new Practical implementation of a person verification system using the profile of 3-dimensional(3D) face images based on weighted Hausdorff distance(WHD) used depth information. The approach works on finding the nose tip have protrusion shape on the face using iterative selection method to use a fiducial feint and extract the profile image from vertical 3D data for the nose tip. Hausdorff distance(HD) is one of usually used measures for object matching. This works analyze the conventional HD and WHD, which the weighted factor is depth information. The Ll measure for comparing two feature vectors were used, because it is simple and robust. In the experimental results, the WHD method achieves recognition rate of 94.3% when the ranked threshold is 5.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.411-417
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• 2021

The field that studies human-computer interaction is called HCI (Human-computer interaction). This field is an academic field that studies how humans and computers communicate with each other and recognize information. This study is a study on hand gesture recognition for human interaction. This study examines the problems of existing recognition methods and proposes an algorithm to improve the recognition rate. The hand region is extracted based on skin color information for the image containing the shape of the human hand, and the center of gravity profile is calculated using principal component analysis. I proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. We proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. The existing center of gravity profile has shown the result of incorrect hand gesture recognition for the deformation of the hand due to rotation, but in this study, the center of gravity profile is used and the point where the distance between the points of all contours and the center of gravity is the longest is the starting point. Thus, a robust algorithm was proposed by re-improving the center of gravity profile. No gloves or special markers attached to the sensor are used for hand gesture recognition, and a separate blue screen is not installed. For this result, find the feature vector at the nearest distance to solve the misrecognition, and obtain an appropriate threshold to distinguish between success and failure.