• 한국측량학회지
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• 제37권3호
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• pp.101-108
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• 2019

최근 컴퓨터 처리 속도의 향상과 영상 처리 기술의 발달로 인해 카메라에서 획득하는 정보를 기존의 GNSS(Global Navigation Satellite System), 추측 항법 기반의 측위 기술과 결합하여 안정적인 위치를 결정하기 위한 연구가 활발히 진행 중이다. 기존 연구에서는 단안 카메라를 이용한 연구가 주로 수행되었으나 이 경우 관심 객체의 절대좌표가 구축이 되어 있어야 한다는 한계점이 있다. 이러한 한계를 극복하기 위해 본 연구에서는 스테레오 영상으로부터 삼각측량법을 적용하여 카메라와 관심 객체간 거리를 추정하는 비전 기반 측위 보조 알고리즘을 개발하고 성능 분석을 수행하였다. 또한, 추정된 거리와 카메라 영상 획득 간격을 이용해 상대적인 속도를 계산하고 이를 기존에 개발된 GNSS/이동체 내부 센서 기반 측위 알고리즘과 결합하여 통합 측위 알고리즘을 구현하였다. 실제 주행 자료를 기반으로 통합측위 알고리즘에 대한 성능을 분석한 결과 기존에 개발된 GNSS/이동체 내부 센서 기반 측위 알고리즘에 비해 속도 정보를 항법해 보정에 활용하였을 때 약 4%의 미미한 위치 정확도 향상 효과를 확인하였다. 이는 영상으로부터 추정된 속도 정보의 정밀도가 낮고, 터널 등을 지날 때는 영상으로부터 적절한 정보를 추출할 수 없다는 한계가 있어 이를 보완한 추가 연구가 필요하다고 판단된다.

• 디지털산업정보학회논문지
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• 제11권3호
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• pp.1-9
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• 2015

In this paper, we implemented the computer vision platform design with MEAN Stack through Raspberry PI 2 model which is an open source platform. we experimented the face recognition, temperature and humidity sensor data logging with WiFi communication under Raspberry Pi 2 model. Especially we directly made the shape of platform with 3D printing design. In this paper, we used the face recognition algorithm with OpenCV software through haarcascade feature extraction machine learning algorithm, and extended the functionality of wireless communication function ability with Bluetooth technology for the purpose of making Android Mobile devices interface. And therefore we implemented the functions of the vision platform for identifying the face recognition characteristics of scanning with PI camera with gathering the temperature and humidity sensor data under IoT environment. and made the vision platform with 3D printing technology. Especially we used MongoDB for developing the performance of vision platform because the MongoDB is more akin to working with objects in a programming language than what we know of as a database. Afterwards, we would enhance the performance of vision platform for clouding functionalities.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2002년도 Proceedings of the International Welding/Joining Conference-Korea
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• pp.314-319
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• 2002

The Automation and Control Group at the University of Brasilia is developing an automatic welding station based on an industrial robot and a controllable welding machine. Several techniques were applied in order to improve the quality of the welding joints. This paper deals with the implementation of a laser-based computer vision system to guide the robotic manipulator during the welding process. Currently the robot is taught to follow a prescribed trajectory which is recorded a repeated over and over relying on the repeatability specification from the robot manufacturer. The objective of the computer vision system is monitoring the actual trajectory followed by the welding torch and to evaluate deviations from the desired trajectory. The position errors then being transfer to a control algorithm in order to actuate the robotic manipulator and cancel the trajectory errors. The computer vision systems consists of a CCD camera attached to the welding torch, a laser emitting diode circuit, a PC computer-based frame grabber card, and a computer vision algorithm. The laser circuit establishes a sharp luminous reference line which images are captured through the video camera. The raw image data is then digitized and stored in the frame grabber card for further processing using specifically written algorithms. These image-processing algorithms give the actual welding path, the relative position between the pieces and the required corrections. Two case studies are considered: the first is the joining of two flat metal pieces; and the second is concerned with joining a cylindrical-shape piece to a flat surface. An implementation of this computer vision system using parallel computer processing is being studied.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.115-120
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• 2000

This study is on the application the image processing algorithm for inspection of the aluminium mill strip surface defect. The image of surface defect data was obtained using the CCD camera with the digital signal board. The edge was found from the difference of pixel intensity between the normal image and defect image. Two step were taken to find the edge in the image processing algorithm. First, noise was removed by using the median filter in the image. Second, the edge was sharpened in detail by using the sharpening convolution filter in the image. Canny algorithm was used to defect the exact edge. The defect section was separated from the original image is to find the coordination point p1 and p2 which include the defect image

• Smart Structures and Systems
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• 제18권3호
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• pp.585-599
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• 2016

Steel cables serve as the key structural components in long-span bridges, and the force state of the steel cable is deemed to be one of the most important determinant factors representing the safety condition of bridge structures. The disadvantages of traditional cable force measurement methods have been envisaged and development of an effective alternative is still desired. In the last decade, the vision-based sensing technology has been rapidly developed and broadly applied in the field of structural health monitoring (SHM). With the aid of vision-based multi-point structural displacement measurement method, monitoring of the tensile force of the steel cable can be realized. In this paper, a novel cable force monitoring system integrated with a multi-point pattern matching algorithm is developed. The feasibility and accuracy of the developed vision-based force monitoring system has been validated by conducting the uniaxial tensile tests of steel bars, steel wire ropes, and parallel strand cables on a universal testing machine (UTM) as well as a series of moving loading experiments on a scale arch bridge model. The comparative study of the experimental outcomes indicates that the results obtained by the vision-based system are consistent with those measured by the traditional method for cable force measurement.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1858-1861
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• 2005

Automatic nut sorting machine used to calculate the size of inserted nut and detect the black spot defection is introduced in this paper. Because most of farm products are imported from the underdeveloped countries, domestic farm products have no place to be sold in market. To overcome this critical situation, lowering the productivity cost is strongly demanded to compete with foreign corps. Imaged processed nut sorting algorithm is developed to the automatic nut sorting machine to remove the sorting time which takes lots of man power. This system is composed of mainly two parts, mechanical parts and vision system. The purpose of mechanical part is supplying the nuts automatically to make computer system capture the images of objects. Simplified mechanical system was assembled followed by 3D simulation by Pro/E design for the adaptive cost effects. Several image processing algorithms are designed to detect the spot defects and calculate the size of nuts. Test algorithm shows good results to the designed automatic nut sorting system.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 춘계학술대회 논문집
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• pp.225-230
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• 2004

A cold ＆ hot rolling coil production line of iron nill consists of a kind of coherent automatic process, but an automatic labelling process still had technical difficulties in the automation of its process. The reason for difficulties in building an automatic process is that quantitative data for each rolled coil from every shipping is not easy to receive from the previous process. it is not possible to apply for a general and simple purpose robot that is actually worked through a taught position to the process because the size and direction of the coi1 has differed on every shipping. From these reasons. we introduce a robot vision system to accept an expected variable situation and to ensure the stability and flexibility of the process. This paper examines a study applied for similar cases and finds the position and direction of relied coil using the moment invariant algorithm proposed by Hu. In addition. the camera calibration and position error compensation algorithm is applied by the analysis of the relationship of transition in a space coordinate system. The construction of a robot vision system proposed by this paper is a more intellectual system than that of the automatic labelling system. which is already used to the Daihen steel nill of NEW JAPAN steel mill co. Ltd in Japan, and shows a better independent operation in the field of production.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1413-1415
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• 2004

This paper proposes a SVM(Support Vector Machine) training algorithm to control a service robot with voice command. The service robot with a stereo vision system and dual manipulators of four degrees of freedom implements a User-Dependent Voice Control System. The training of SVM algorithm that is one of the statistical learning theories leads to a QP(quadratic programming) problem. In this paper, we present an efficient SVM speech recognition scheme especially based on less learning data comparing with conventional approaches. SVM discriminator decides rejection or acceptance of user's extracted voice features by the MFCC(Mel Frequency Cepstrum Coefficient). Among several SVM kernels, the exponential RBF function gives the best classification and the accurate user recognition. The numerical simulation and the experiment verified the usefulness of the proposed algorithm.

• 제어로봇시스템학회논문지
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• 제12권11호
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• pp.1156-1161
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• 2006

This paper describes a fast image labeling algorithm for the feature extraction of connected components. Labeling the connected regions of a digitized image is a fundamental computation in image analysis and machine vision, with a large number of application that can be found in various literature. This algorithm is designed for the surface defect inspection of Cold Mill Strip. The labeling algorithm permits to separate all of the connected components appearing on the Cold Mill Strip.

• 대한기계학회논문집A
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• 제21권8호
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• pp.1339-1347
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• 1997

The automation of final inspection and tuning process in the manufacturing of electric products is hot issue now, because it is the only part that has not been wholey automized yet, mainly due to the difficulties to handle so small size of VR which is the final tuning point in the most of electric products. For the automation of this process, at first the accurate measurement of position and orientation of SMD VR on PCB in real time is strongly needed. In this paper, a new image processing algorithm to detect the center position and orientation of target VR by using machine vision is proposed for automatic final tuning of the 8mm camcoder's performance. In the method, the outline feature of object is used actively. The usefulness of the proposed methods were tested by several experiments, and the results showed enough accuracy for both of position and orientation. Additatively, we discussed about the total visual system construction and preprocessing of image.