• 비파괴검사학회지
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• 제10권1호
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• pp.10-17
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• 1990

Recently, object recognition ultrasonic sensor is being used with automatization of industrial machine. Points which characterize the object can be deleted by measuring the propagation time of ultrasonic impulse and azimuth which gives its maximum amplitude, and from these points shape, position and orientation of the object are deduced. A new measuring method is adopted, where the distance to the object is calculated by sound reflection time which is measured from O-cross point of sound wave, and azimuth is measured by angle indicating maximum amplitude. The measuring accuracy of 1.0mm for distance and $0.5-2^{\circ}$ for azimuth have been accomplished. By rotational scanning of sensor the characteristic point of an object can be known and it gives the information of its shape, position and orientation. Experimental results showed that the object of some complicated shape can be recognized, which suggest its applicability to robot.

• International Journal of Advanced Culture Technology
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• 제6권3호
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• pp.142-150
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• 2018

This paper describes the algorithm that lowers the dimension, maintains the object recognition and significantly reduces the eigenspace configuration time by combining the edge orientation histogram and principle component analysis. By using the detected object region as a recognition input image, in this paper the object recognition method combined with principle component analysis and the multi-layer network which is one of the intelligent classification was suggested and its performance was evaluated. As a pre-processing algorithm of input object image, this method computes the eigenspace through principle component analysis and expresses the training images with it as a fundamental vector. Each image takes the set of weights for the fundamental vector as a feature vector and it reduces the dimension of image at the same time, and then the object recognition is performed by inputting the multi-layer neural network.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.62-67
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• 2005

Object recognition in the field of robotics generally has depended on a computer vision system. Recently, RFID(Radio Frequency IDentification) technology has been suggested to support recognition and has been rapidly and widely applied. This paper introduces the more advanced RFID-based recognition. A novel tag named 3D tag, which facilitates the understanding of the object, was designed. The previous RFID-based system only detects the existence of the object, and therefore, the system should find the object and had to carry out a complex process such as pattern match to identify the object. 3D tag, however, not only detects the existence of the object as well as other tags, but also estimates the orientation and position of the object. These characteristics of 3D tag allows the robot to considerably reduce its dependence on other sensors required for object recognition the object. In this paper, we analyze the 3D tag's detection characteristic and the position and orientation estimation algorithm of the 3D tag-based RFID system.

• 대한전자공학회논문지
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• 제27권5호
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• pp.757-766
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• 1990

In this paper a new knowledge based vision system using orientation information on each surface of the 3-dimensional object is discussed. The measurement of the orientation information is performed by photometric stereo method. And then the obtained orientations are segmented using Gaussian curvature and mean curvature. A hierarchical knowledge base which is based on the characteristics, shape, area and length of the surface is built up, and then the knowledge based system infers by the condition interprete system (CIS). As the results, an easier and more accurate 3-D object recognition system is implemented, because it uses the characteristics and shapes as units of the surface in the recognition process.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1200-1207
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• 2017

Sensors in a smartphone can be used to measure various physical quantities. In this paper, we propose an object localization scheme in a three dimenstional using a smart phone. The proposed scheme estimates the location of an object by observing it from several different points. The direction to the target object and the locations of the observation points are collected at each observation point using the location sensor and the orientation sensor in the smartphone. Based on these observations, the proposed scheme derives three dimensional line of sight vectors and estimates the location of the target object that minimizes the estimation error. We implemented the proposed scheme on an Android smartphone and tested its performance by estimating the height of a building and characteristics of the proposed approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4534-4555
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• 2015

We propose a robust object cataloging method using multiple locally distinct heterogeneous features for aiding image retrieval. Due to challenges such as variations in object size, orientation, illumination etc. object recognition is extraordinarily challenging problem. In these circumstances, we adapt local interest point detection method which locates prototypical local components in object imageries. In each local component, we exploit heterogeneous features such as gradient-weighted orientation histogram, sum of wavelet responses, histograms using different color spaces etc. and combine these features together to describe each component divergently. A global signature is formed by adapting the concept of bag of feature model which counts frequencies of its local components with respect to words in a dictionary. The proposed method demonstrates its excellence in classifying objects in various complex backgrounds. Our proposed local feature shows classification accuracy of 98% while SURF,SIFT, BRISK and FREAK get 81%, 88%, 84% and 87% respectively.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.1929-1930
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• 2006

Human like robot arm posture for grasping by considering the shape of the target object is quite a challenge in the field of robotics. In this paper, an optimized grasp posture with respect to the shape of the object considering the wrist joint angle and elbow elevation angle, in order to verify that the grasp posture is human like has been proposed. Given a target object, the candidates for grasp are computed by the method described in this paper. For each candidate, the closed loop inverse kinematics has been solved for the corresponding hand position and orientation. From the obtained joint angles through inverse kinematics, the elbow elevation angle has been computed and compared with the elbow elevation angle obtained through human movement data by the characteristic equation. After considering all the candidates, the hand position and orientation with minimum wrist joint and difference in elbow elevation angles has been utilized as the optimized grasp posture. Simulation results are presented.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.500-503
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• 1997

In this paper, a method for recognizing 3-D objects using the 3-D Hough transform and the robust stereo vision is studied. A 3-D object is recognized through two steps; modeling step and matching step. In modeling step, features of the object are extracted by analyzing the IGES file. In matching step, the values of the sensed image are compared with those of the IGES file which is assumed to location and orientation in the 3-D Hough transform domain. Since we use the 3-D Hough transform domain of the input image directly, the sensitivity to the noise and the high computational complexity could be significantly allcv~ated. Also, the cost efficiency is improved using the robust stereo vision for obtaining depth map image which is needed for 3-D Hough transform. In order lo verify the proposed method, real telephone model is recognized. Thc results of the location and orientation of the model are presented.

• 감성과학
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• 제11권4호
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• pp.501-510
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• 2008

규범적 표상은 단어나 주제가 주어졌을 때 자연스럽게 떠오르는 심상이다. 이러한 규범적 표상은 대상의 특징을 가장 잘 드러낼 수 있는 특정한 조망이나 방향으로 떠오르게 된다. 규범적 표상이 측면임을 시사하는 선행 연구를 바탕으로 본 연구에서는 규범적 표상의 방향성을 검토하였다. 규범적 표상을 자연범주와 인공범주로 구분하여 자극의 제시 방향에 따른 차이를 알아보았다. 실험은 그림의 방향성(왼쪽/오른쪽)과 범주(동물, 자연범주/도구, 인공범주)를 두 가지 독립변인으로 하여 설계하였으며 단어-그림 일치 판단과제를 사용하여 정답 반응률과 반응시간을 측정하였다. 그 결과, 정답 반응률은 범주 내에서 방향성에 따른 모든 조건에서 천장효과를 보였으며 아주 근소한 차이만 있었다. 반응시간에서 범주변인의 주효과, 범주와 방향성의 상호작용 효과가 나타났다. 특히 자연범주에 속하는 동물 그림에서 방향성 효과가 관찰되었다. 동물의 머리가 왼쪽으로 향하는 그림이 오른쪽으로 향하는 그림 보다 반응시간이 유의하게 빨랐다. 그러나 인공범주에 속하는 도구 그림에서는 방향성의 효과가 나타나지 않았다. 이러한 결과는 동물의 규범적 표상의 방향성은 왼쪽을 향하는 것임을 시사한다.

• 전자공학회논문지B
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• 제29B권7호
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• pp.52-61
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• 1992

본 논문은 단시안에 투영된 3차원 물체의 Image에서 측정된 명암강도의 차이를 이용하여 3차원 물체의 절대거리 z 및 형상을 유출하는 수치적인 방법을 연구, 단시안에 의해서도 Camera와 물체사이의 3차원 절대거리가 구해질 수 있음을 보여주고 있다. 기발표된 이론과는 다르게 본 논문에서는 점광원을 이용하여 투영된 명암강도와 3차원 물체의 절대거리 및 형상과의 관계를 물체가 Uniform Lambertian이라는 가정하에서 새로운 관계식으로 정립하였다. 정립된 Non-Linear 관계식은 Smoothness 조건아래 $'Calculus of Variation$'방법을 사용하여 수학적 Algorithm으로 정리되어 Programming 되었고 간단한 실험방법을 이용하여 실제 Data에 적용시켜 그 타당성을 조사하였다.당성을 조사하였다.