• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.809-813
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• 2004

In this paper, we developed a network camera for CMOS camera module inspection. The design, implementation details including embedded linux porting and CPLD logics, and performance of network camera are described. The network camera consists of SoC(S3C4530A), CPLD and CMOS image sensor. In order to image data of CMOS image sensor we designed capture logics on CPLD by using VHDL program. Embedded Linux such as uClinux is performed on the network camera to utilize development environment and TCP/IP protocol specification. The application is based on socket communication between GUI on PC and Embedded Linux based network camera. When JPEG compression is applied, the transmission speed was improved enough for this system to be used for an alternative of expensive CCTV or remote monitoring system in a power plant and uninhabited places.

• Journal of Environmental Health Sciences
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• v.34 no.1
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• pp.95-100
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• 2008

An automatic titration system using a PC-camera with a color filter on its lens was used in the $KMnO_4$ consumption test of tap water and distilled water in relation to blank tests. The very faint pink color of titration end point could be effectively detected by using a yellow cellophane paper as a color filter. The average hue value (Havg) of 192 pixels in the image of the sample solution being titrated was computed and followed up at regular time intervals during titration in order to detect the titration end point. The Havg decrease of 2 degrees from the average of first 10 Havgs was regarded as reaching the end point. The volume of 0.01N $KMnO_4$ consumed by a tap water sample was $0.728{\pm}0.022ml$ in manual titration and $0.735{\pm}0.013ml$ in automatic titration (p=0.580). The volume of 0.01N $KMnO_4$ consumed by a distilled water sample was $0.383{\pm}0.015ml$ in manual titration and $0.367{\pm}0.015ml$ in automatic titration (p=0.252). The high p-values for t-test suggested that there were good agreements between manual and automatic titration data and the automatic method proposed in this article was considered to effectively replace the manual titration.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.331-334
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• 2002

In this paper, we present two types of vision algorithm that mobile robot has CCD camera. for obstacle avoidance. This is simple algorithm that compare with grey level from input images. Also, The mobile robot depend on image processing and move command from PC host. we has been studied self controlled mobile robot system with CCD camera. This system consists of digital signal processor, step motor, RF module and CCD camera. we used wireless RF module for movable command transmitting between robot and host PC. This robot go straight until recognize obstacle from input image that preprocessed by edge detection, converting, thresholding. And it could avoid the obstacle when recognize obstacle by line histogram intensity. Host PC measurement wave from various line histogram each 20 Pixel. This histogram Is ( x , y ) value of pixel. For example, first line histogram intensity wave from ( 0, 0 ) to ( 0, 197 ) and last wave from ( 280, 0 ) to ( 280, 197 ). So we find uniform wave region and nonuniform wave region. The period of uniform wave is obstacle region. we guess that algorithm is very useful about moving robot for obstacle avoidance.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.705-717
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• 2001

In this paper, we propose a rapid lane detection method to extract a preceding vehicle from sequential images captured by a single monocular CCD camera. We detect positions of lanes for an individual image within the limited area that would not be hidden and thereby compute the slopes of the detected lanes. Then we find a search area where vehicles would exist and extract the position of the preceding vehicle within the area with edge component by applying a structured method. To verify the effects of the proposed method, we capture the road images with a notebook PC and a CCD camera for PC and present the results such as processing time for lane detection, accuracy and vehicles detection against the images.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.5
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• pp.529-535
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• 2009

This paper describes a measuring device of glass thickness using machine vision and image processing techniques on real-time. Today, the machine vision enable to inspect fast and exactly than human's eyes. The presented system has advantages of continuous measurement, flexibility and good accuracy. The system consists of a laser diode, a CCD camera with PC. The camera located on the opposite side of the incident beam measures the distance between two reflected laser beams from the glass top and bottom surface. We apply a binary algorithm to convert and analyze the image from camera to PC. Laser point coordination by border tracing algorithm is used to find the center of beam circle. The measured result was compared with micrometer and showed 0.002mm accuracy. Finally, the errors were discussed how to minimize the influence of glass wedge angle and angular error of moving stage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.453-458
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• 2016

One of the most common applications of machine vision is quality inspections in automated production. In this study, a welding inspection system that is controlled by a PC and a PLC equipped with a multi-camera setup was developed. The system was designed to measure the primary dimensions, such as the length and width of the welding areas. The TCP/IP protocols and multi-threading techniques were used for parallel control of the optical components and physical distribution. A coaxial light was used to maintain uniform lighting conditions and enhance the image quality of the weld areas. The core image processing system was established through a combination of various algorithms from the OpenCV library. The proposed vision inspection system was fully validated for an actual weld production line and was shown to satisfy the functional and performance requirements.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.303-305
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• 2015

본 연구에서는 불법 주 정차 단속을 위한 번호판 인식용 스피드돔 카메라 개발을 위한 선행 연구로 전체 목표 중 PC와 카메라 모듈간 통신 Board 제작과 소니의 FCB-EX1010 카메라 기능 확인을 위한 PC S/W 구성, VISCA/RS232C Command 확인 및 One Board 작성에 필요한 사전 PC 용 프로그램 구성과 VISCA 통신 Format을 이용한 통신 프로그램을 구성하고 평가하였다. 구성한 통신 보드와 프로그램, 통신 Format은 정상 작동하도록 완성하였으며, 결합한 테스트에서 통신 향후 다양한 주의할 점과 목표를 찾아내었다. 정밀 장거리 스피드 돔 카메라 요구가 많아지고 있는 시점에서 적정한 개발을 위한 선행 연구이었다.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.5
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• pp.78-85
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• 2006

Thanks to the spacial and timely flexibility of laboratory's environment, the distance learning based real time PLC education system has been brought into relief as a next generation laboratory alternative. The developed system was installed using a relatively cheap PLC and PC camera. Providing image feedback through the PC camera, the system provides the student's interests of the lab as well as an opportunity to monitor the lab's activities and results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.157-163
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• 2016

This paper presents Finger Keyboard which detects the user's key types on a keyboard drawn on the paper using a video camera. The Finger Keyboard software was written in standard C/C++ language and thus easy to port to other computing environments. We installed a popular USB-type web camera on a Windows PC and implemented the Finger Keyboard as a Windows application which detects key typing and then injects the key code into the message queue of the Windows operating system. Also we implemented the Finger Keyboard on the Raspberry Pi 2 embedded computer with a dedicated camera and connected it to the Android device as an external keyboard through the Bluetooth. The result of experiments showed that the average ratio of recognition success is around 80% at the typing speed of 120 characters per minute.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.435-442
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• 2018

This study implemented an FPGA-based system to extract PCB defect patterns. The FPGA-based system can perform pattern matching at high speed for vision automation. An image processing library that is used to extract defect patterns was also implemented in IPs to optimize the system. The IPs implemented are Camera Link IP, Histogram IP, VGA IP, Horizontal Projection IP and Vertical Projection IP. In terms of hardware, the FPGA chip from the Vertex-5 of Xilinx was used to receive and handle images that are sent from a digital camera. This system uses MicroBlaze CPU. The image results are sent to PC and displayed on a 7inch TFT-LCD and monitor.