• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.518-523
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• 2005

Strip off-center is one of the major problems in hot strip mill line. The key to good centering is having good equipment, modern control systems, excellent maintenance and an understanding of milling process. Therefore, this study aims to develop a system that is useful for quantitative analysis of strip off-center. In this study, the measuring method of strip off-center was thoroughly studied and the exclusive control board to line scan camera were designed. Also, the manipulated type housing for line scan camera was developed to adjust initial parameters for strip width and center line. In order to check the accuracy and usefulness of the developed system, FM stand in $\#2$ Hot Strip Factory in Pohang Steel Works was targeted.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.12
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• pp.1036-1040
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• 2002

To process data of digital linescan camera, the frame grabber is essential to handle the data in low-level and in high speed more than 30 MHz stably. Traditional approaches to the development of hardware in vision system for the special purpose are mai y based on PC system, and are expensive and gigantic. Therefore, there are many difficulties in applying those in the field. So we investigate, in this paper, the implementation of FPGA for real-time processing of digital linescan camera. The system is not based on PC, but electronic device such as micropncessor. So it is expected that the use of FPGAs for low-level processing represents a fast, stable and inexpensive system. The experiments are carried out on the web guiding system in order to show the efficiency of the new image processor.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.2
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• pp.25-31
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• 2009

The image processing methods are widely used in many industrial fields to detect defections in inspection devices. In this study an image processing method was conducted for the detection of abnormal pixels in a OLED(Organic Light Emitting Diode) type panel which is used for small size displays. The display quality of an OLED device is dependent on the pixel formation quality. So, among the so many pixels, to find out the faulty pixels is very important task in manufacturing processing or inspection division. We used a line scanning type BW(Black & White) camera which has very high resolution characteristics to acquire an image of display pixel patterns. And the various faulty cases in pixel abnormal patterns are considered to detect abnormal pixels. From the results of the research, the normal BW pixel image could be restored to its original color pixel.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.103-104
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• 2015

본 논문에서는 모형 차량을 이용하여 자율주행 시스템을 구현하고자 한다. 이 시스템의 목적은 차선을 계속 유지함으로써 자율주행을 하는데 있다. 이를 위하여 32비트 마이크로프로세서를 이용한 모형차량을 설계하고 흰 바탕과 검은색 차선으로 이루어진 환경에서 시뮬레이션을 통해 살펴본다. 라인스캔 카메라(TSL1401CL)를 사용하여 차선을 인식하고 이에 따라 자율주행을 하는 시스템을 구현한다.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.333-334
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• 2007

We propose a path planning method to decrease a inspection lead time of line scan camera in SMT(surface mount technology) in-line system. The inspection window area of printed circuit board should be minimized to consider the FOV(field of view) of line scan camera so that line scan inspector is going to find a optimal solution of path planning. We propose one of the hierarchical clustrering algorithm for a given board. Comparative simulation results are presented to verify the usefulness of proposed method.

• Annual Conference of KIPS
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• 2002.11a
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• pp.687-690
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• 2002

본 논문은 자동으로 볼트를 검사할 수 있는 장치에 대한 시스템 설계 및 제품 개발에 관해 다룬다. 볼트를 연속적으로 검사하기 위해 컨베이어를 이용하고 이를 동작시키기 위한 서보모터와 엔코더를 부착하여 정확한 이송량를 유지하게 된다. 엔코더 신호를 수신한 라인스캔 카메라의 동작에 따라 프레임 그래버로 볼트 영상을 전송하며 한 프레임을 구성한 후 영상 검사 알고리즘에 의해 파라메터를 측정하고 검사하게 된다. 제작된 결과물을 이용하여 실험을 통해 본 장치의 효용성을 입증하고자 한다.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.13-21
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• 2018

AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.852-859
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• 2009

Normally, to extract the defect in TFT-LCD inspection system, the image is obtained by using line scan camera or area scan camera which is achieved by CCD or CMOS sensor. Because of the limited dynamic range of CCD or CMOS sensor as well as the effect of the illumination, these images are frequently degraded and the important features are hard to decern by a human viewer. In order to overcome this problem, the feature vectors in the image are obtained by using the average intensity difference between defect and background based on the weber's law and the standard deviation of the background region. The defect detection method uses non-linear SVM (Supports Vector Machine) method using the extracted feature vectors. The experiment results show that the proposed method yields better performance of defect classification methods over conveniently method.

• Journal of Digital Convergence
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• v.16 no.3
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• pp.303-309
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• 2018

Computer vision technology is a component inspection to obtain a video image from the camera to the machine to perform the capabilities of the human eye with a field of artificial intelligence, and then analyzed by the algorithm to determine to determine the good and bad of production parts It is widely applied. Shape inspection method was used as how to identify the location of the start point and the end point of the search range, measure the height to the line scan method, in such a manner as to determine the presence or absence of the bolt tabs average brightness of the inspection area in a circular scan type value And the degree of similarity was calculated. The total time it takes to test in the test performance tests of two types of bolts tab enables test 300 min, and demonstrated the accuracy and efficiency of the inspection on the production line represented a complete inspection accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.793-799
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• 2007

Generally, a semiconductor chip measured with a few micro units is captured by line scan camera for higher inspection accuracy. However, the faulty inspection requires an exact boundary detection algorithm, because it is very sensitive to scan speed and lighting conditions. In this paper we propose boundary detection with subpixel edge detection in order to increase the accuracy of bump faulty detection on chips. The bump edge is detected by first derivative to four directions from bump center point and the exact edge positions are searched by the subpixel method. Also, the exact bump boundary to calculate the actual bump size is computed by LSM(Least Squares Method) to minimize errors since the bump size is varied such as bump protrusion, bump bridge, and bump discoloration. Experimental results exhibit that the proposed algorithm shows large improvement comparable to the other conventional boundary detection algorithms.