• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1920-1925
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• 2004

This paper describes a new method for 3D object recognition which used surface segment-based stereo vision. The position and orientation of an objects is identified accurately enabling a robot to pick up, even though the objects are multiple and partially occluded. The stereo vision is used to get the 3D information as 3D sensing, and CAD model with its post processing is used for building models. Matching is initially performed using the model and object features, and calculate roughly the object's position and orientation. Though the fine adjustment step, the accuracy of the position and orientation are improved.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.420-425
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• 2003

Generally, reverse engineering means getting CAD data from unidentified shape using vision or 3D laser scanner system. In this paper, we studied unidentified model by machine vision based reverse engineering system to get information about in-processing model. Recently, vision technology is widely used in current factories, because it could inspect the in-process object easily, quickly, accurately. The following tasks were mainly investigated and implemented. We obtained more precise data by corning camera's distortion, compensating slit-beam error and revising acquired image. Much more, we made similar curves or surface with B-spline approximation for precision. Until now, there have been many case study of shape recognition. But it was uncompatible to apply to the field, because it had taken too many processing time and has frequent recognition failure. This paper propose recognition algorithm that prevent such errors and give applications to the field.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 춘계학술대회 논문집
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• pp.553-558
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• 2008

Advancement in information technology have enabled applying vision sensor to railway, such as CCTV. CCTV has been widely used in railway application, however the CCTV is a passive system that provide limited capability to maintain safety from boarding platform. The station employee should monitor continuously CCTV monitors. Therefore immediate recognition and response to the situation is difficultin emergency situation. Recently, urban transit operators are pursuing applying an unattended station operation system for their cost reduction. Therefore, an intelligent monitoring system is need for passenger's safety in railway. The paper proposes a vision based monitoring system and object detection algorithm for passenger's safety in railway platform. The proposed system automatically detects accident in platform and analyzes level of danger using image processing technology. The system uses stereo vision technology with multi-sensors for minimizing detection error in various railway platform conditions.

• 한국컴퓨터정보학회논문지
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• 제24권5호
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• pp.59-66
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• 2019

According to the KT telecommunication statistics, people stayed inside their houses on an average of 11.9 hours a day. As well as, according to NSC statistics in the united states, people regardless of age are injured for a variety of reasons in their houses. For purposes of this research, we have investigated an abnormal event detection algorithm to classify infrequently occurring behaviors as accidents, health emergencies, etc. in their daily lives. We propose a fusion method that combines three classification algorithms with vision pattern, audio pattern, and activity pattern to detect unusual user events. The vision pattern algorithm identifies people and objects based on video data collected through home CCTV. The audio and activity pattern algorithms classify user audio and activity behaviors using the data collected from built-in sensors on their smartphones in their houses. We evaluated the proposed individual pattern algorithm and fusion method based on multiple scenarios.

• JSTS:Journal of Semiconductor Technology and Science
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• 제12권2호
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• pp.212-218
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• 2012

A stereo vision is able to build three-dimensional maps of its environment. It can provide much more complete information than a 2D image based vision but has to process, at least, that much more data. In the past decade, real-time stereo has become a reality. Some solutions are based on reconfigurable hardware and others rely on specialized hardware. However, they are designed for their own specific applications and are difficult to extend their functionalities. This paper describes a vision system based on a System on a Chip (SoC) platform. A real-time stereo image correlator is implemented using Sum of Absolute Difference (SAD) algorithm and is integrated into the vision system using AMBA bus protocol. Since the system is designed on a pre-verified platform it can be easily extended in its functionality increasing design productivity. Simulation results show that the vision system is suitable for various real-time applications.

• Journal of Information Processing Systems
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• 제16권1호
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• pp.155-170
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• 2020

Passive ranging is a critical part of machine vision measurement. Most of passive ranging methods based on machine vision use binocular technology which need strict hardware conditions and lack of universality. To measure the distance of an object placed on horizontal plane, we present a passive ranging method based on monocular vision system by smartphone. Experimental results show that given the same abscissas, the ordinatesis of the image points linearly related to their actual imaging angles. According to this principle, we first establish a depth extraction model by assuming a linear function and substituting the actual imaging angles and ordinates of the special conjugate points into the linear function. The vertical distance of the target object to the optical axis is then calculated according to imaging principle of camera, and the passive ranging can be derived by depth and vertical distance to the optical axis of target object. Experimental results show that ranging by this method has a higher accuracy compare with others based on binocular vision system. The mean relative error of the depth measurement is 0.937% when the distance is within 3 m. When it is 3-10 m, the mean relative error is 1.71%. Compared with other methods based on monocular vision system, the method does not need to calibrate before ranging and avoids the error caused by data fitting.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권1호
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• pp.27-34
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• 2015

For a vision-based driver assistance system, unusual motion detection is one of the important means of preventing accidents. In this paper, we propose a real-time unusual-motion-detection model, which contains two stages: salient region detection and unusual motion detection. In the salient-region-detection stage, we present an improved temporal attention model. In the unusual-motion-detection stage, three kinds of factors, the speed, the motion direction, and the distance, are extracted for detecting unusual motion. A series of experimental results demonstrates the proposed method and shows the feasibility of the proposed model.

• 한국공작기계학회논문집
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• 제15권5호
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• pp.37-43
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• 2006

The target of this study is development of web based mold discrimination system by matching vision information with CAD database. The use of 2D vision image makes possible speedy mold discrimination from many databases. The image processing such as preprocessing, cleaning is done for obtaining vivid image with object information. The web-based system is a program which runs to exchange messages between a server and a client by making of ActiveX control and the result of mold discrimination is shown on web-browser. For effective feature classification and extraction, signature method is used to make sensible information from 2D data. As a result, the possibility of proposed system is shown as matching feature information from vision image with CAD database samples.

• 한국전자통신학회논문지
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• 제13권2호
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• pp.457-462
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• 2018

국내 철도운영기관에서는 고속화 무인화에 따른 보다 효율적이고 더욱 스마트한 운영, 유지보수 및 관리를 위한 시스템을 절실히 필요로 하고 있다. 따라서 영상기반 기술을 국내 철도산업에 적용한 지능형 운영, 유지보수 및 관리 시스템 개발을 위한 많은 연구들이 있다. 본 논문에서는 철도안전시스템, 철도차량 유지보수, 그리고 철도시설물 관리를 위한 지능형 시스템을 개발하기 위하여 영상기반 기술을 사용한 국내 연구들을 분석한다. 그리고 딥러닝 기술 등이 사용된 보다 강력한 영상기반 기술을 적용하여 철도운영기관에서 필요한 시스템을 개발하는 연구의 방향을 제시한다.

• Smart Structures and Systems
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• 제3권3호
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• pp.373-384
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• 2007

For structural health monitoring (SHM) of civil infrastructures, displacement is a good descriptor of the structural behavior under all the potential disturbances. However, it is not easy to measure displacement of civil infrastructures, since the conventional sensors need a reference point, and inaccessibility to the reference point is sometimes caused by the geographic conditions, such as a highway or river under a bridge, which makes installation of measuring devices time-consuming and costly, if not impossible. To resolve this issue, a visionbased real-time displacement measurement system using digital image processing techniques is developed. The effectiveness of the proposed system was verified by comparing the load carrying capacities of a steel-plate girder bridge obtained from the conventional sensor and the present system. Further, to simultaneously measure multiple points, a synchronized vision-based system is developed using master/slave system with wireless data communication. For the purpose of verification, the measured displacement by a synchronized vision-based system was compared with the data measured by conventional contact-type sensors, linear variable differential transformers (LVDT) from a laboratory test.