• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.69-72
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• 2011

본 논문에서는 방향 연결성 추적을 이용한 의사 특징점 제거에 관하여 연구하였다. 특징점을 추출하는 방법에는 교차수를 이용한 방법이 있다. 그러나 교차수를 이용한 방법에서는 의사 특징점이 많이 추출된다. 교차수를 이용한 방법에서 잘못 추출된 특징점들을 방향 연결성 추적을 이용한 의사 특징점 제거 알고리즘을 이용하여 의사 특징점을 제거하였다. 성능 평가를 위하여 교차수를 이용한 방법과 방향 연결성 추적을 이용하여 추출된 실제 특징점을 비교하였으며, 실험결과 방향 연결성 추적을 이용하여 많은 의사 특징점이 제거되었음을 알 수 있었다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.382-393
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• 1991

In this paper, we propose a method for recognizing printed Korean characters using the Preceding Layer Driven multi-layer perceptron. The new learning algorithm which assigns the weight values to an integer and makes use of the transfer function as the step function was presented to design the hardware. We obtained 522 Korean character-image as an experimental object through scanner with 600DPI resolution. The preprocessing for feature extraction of Korean character is the separation of individual character, noise elimination smoothing, thinnig, edge point extraction, branch point extraction, and stroke segmentation. The used feature data are the number of edge points and their shapes, the number of branch points, and the number of strokes with 8 directions.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.149-156
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• 2005

In the actuality that the various services are provided in connection with the network of internet by activating the communication using Propagation, the importance of the feature point and chase of an object is greatly raised to increase the quality of the detection and tracking of the communication service. This paper is to detect the shadow space by using Snakes Algorithms and Present a system's base which tracts the route from start to target points in the detected shadow space as a study for the detection and tracking the shadow space which does not reach the propagation.

• Journal of Integrative Natural Science
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• v.5 no.2
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• pp.120-126
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• 2012

This paper describes the algorithm that lowers the dimension, maintains the gesture recognition and significantly reduces the eigenspace configuration time by combining the higher correlation feature information and Principle Component Analysis. Since the suggested method doesn't require a lot of computation than the method using existing geometric information or stereo image, the fact that it is very suitable for building the real-time system has been proved through the experiment. In addition, since the existing point to point method which is a simple distance calculation has many errors, in this paper to improve recognition rate the recognition error could be reduced by using several successive input images as a unit of recognition with K-Nearest Neighbor which is the improved Class to Class method.

• Journal of Integrative Natural Science
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• v.1 no.2
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• pp.133-139
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• 2008

Face recognition technologies using PCA(principal component analysis) recognize faces by deciding representative features of faces in the model image, extracting feature vectors from faces in a image and measuring the distance between them and face representation. Given frequent recognition problems associated with the use of point-to-point distance approach, this study adopted the K-nearest neighbor technique(class-to-class) in which a group of face models of the same class is used as recognition unit for the images inputted on a continual input image. This paper proposes a new PCA recognition in which database of faces.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.465-472
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• 2015

This paper presents a visual touch recognition for NUI(Natural User Interface) using Voronoi-tessellation algorithm. The proposed algorithms are three parts as follows: hand region extraction, hand feature point extraction, visual-touch recognition. To improve the robustness of hand region extraction, we propose RGB/HSI color model, Canny edge detection algorithm, and use of spatial frequency information. In addition, to improve the accuracy of the recognition of hand feature point extraction, we propose the use of Douglas Peucker algorithm, Also, to recognize the visual touch, we propose the use of the Voronoi-tessellation algorithm. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.177-182
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• 1997

A visual servoing method is proposed for a robot with a camera in hand. Specifically, vanishing point features are suggested by employing a viewing model of perspective projection to calculate the relative rolling, pitching and yawing angles between the object and the camera. To compensate dynamic characteristics of the robot, desired feature trajectories for the learning of visually guided line-of-sight robot motion are obtained by measuring features by the camera in hand not in the entire workspace, but on a single linear path along which the robot moves under the control of a commercially provided function of linear motion. And then, control actions of the camera are approximately found by fuzzy-neural networks to follow such desired feature trajectories. To show the validity of proposed algorithm, some experimental results are illustrated, where a four axis SCARA robot with a B/W CCD camera is used.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.79-80
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• 2024

인공지능과 디지털 변환의 추세가 소매업계에서 온라인으로의 전환을 가속화하고 있다. 이러한 변화에 부응하여 본 논문에서는 O2O(Online-to-Offline) 상점을 위한 상품명 인식 기술을 제안한다. 제안하는 방법은 이미지 내 특징점과 이들 주변의 픽셀 정보를 포함하는 특징 디스크립터를 활용하여 상품 이미지와 진열대 사진을 비교하는 것에 초점을 맞춘다. 사용된 주요 알고리즘은 SURF와 BFMatcher, KnnMatch 방법으로, 이들은 각각 이미지의 특징점을 탐지하고 매칭하는 데 사용된다. 실험을 통해 적절한 임계값을 설정하여 높은 신뢰도의 매칭 결과를 선별하는 방법을 제시하였으며, 이를 통해 O2O 상점에서 상품 관리와 인식을 향상시키는 데 기여할 수 있다.

• Genomics & Informatics
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• v.18 no.1
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• pp.2.1-2.11
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• 2020

In this paper, we propose a new approach to detecting outliers in a set of segmented genomes of the flu virus, a data set with a heterogeneous set of sequences. The approach has the following computational phases: feature extraction, which is a mapping into feature space, alignment-free distance measure to measure the distance between any two segmented genomes, and a mapping into distance space to analyze a quantum of distance values. The approach is implemented using supervised and unsupervised learning modes. The experiments show robustness in detecting outliers of the segmented genome of the flu virus.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.260-263
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• 1996

THe Purpose of this paper is to match the feature point of man-made structure and to obtain the DEM which are occluded in a image plane. We use the trinocular matching with epipolar lines and planes. If an occlusion appears at one of the trinocular images, the DEM mapping is used to estimate the height of feature points in it.