• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.119-124
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• 1999

This paper presents new approach to technology pattern recognition of camera back cover and test of soldering. In real-time implementing of pattern recognition camera back cover and test of soldering, the MVB-03 vision board has been used. Image can be captured from standard CCD monochrome camera in resolutions up to 640$\times$480 pixels. Various options re available for color cameras, a synchronous camera reset, and linescan cameras. Image processing os performed using Texas Instruments TMS320C31 digital signal processors. Image display is via a standard composite video monitor and supports non-destructive color overlay. System processing is possible using c30 machine code. Application software can be written in Borland C++ or Visual C++

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.28-33
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• 2012

The visual sensing of human hands plays an important part in many man-machine interaction/interface systems. Most existing visionbased hand detection techniques depend on the color cues of human skin. The RGB color image from a vision sensor is often transformed to another color space as a preprocessing of hand detection because the color space transformation is assumed to increase the detection accuracy. However, the actual effect of color space transformation has not been well investigated in literature. This paper discusses a comparative evaluation of the pixel classification performance of hand skin detection in four widely used color spaces; RGB, YIQ, HSV, and normalized rgb. The experimental results indicate that using the normalized red-green color values is the most reliable under different backgrounds, lighting conditions, individuals, and hand postures. The nonlinear classification of pixel colors by the use of a multilayer neural network is also proposed to improve the detection accuracy.

• ETRI Journal
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• v.33 no.3
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• pp.415-422
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• 2011

In this paper, we present a novel vision-based method of recognizing finger actions for use in electronic appliance interfaces. Human skin is first detected by color and consecutive motion information. Then, fingertips are detected by a novel scale-invariant angle detection based on a variable k-cosine. Fingertip tracking is implemented by detected region-based tracking. By analyzing the contour of the tracked fingertip, fingertip parameters, such as position, thickness, and direction, are calculated. Finger actions, such as moving, clicking, and pointing, are recognized by analyzing these fingertip parameters. Experimental results show that the proposed angle detection can correctly detect fingertips, and that the recognized actions can be used for the interface with electronic appliances.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.390-393
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• 2005

he FPCs(Flexible Printed Circuit) are currently used in several electronic products like digital cameras, cellular phones because of flexible material characteristics. Because the FPC is usually small size and flexible, only one FPC should not enter chip mounting process, instead, several FPCs is placed on the large rigid pallette and go to the chip mounting process. Currently the job of mounting FPC on the pallette is carried by totally manual way. Thus, the goals of the research is develop the automatic machine of FPC mounting on pallette using vision alignment. The procedure of operating machine is firstly to measure alignment error of FPC, correct alignment errors, and finally mount well-aligned FPC on the pallette. The vision technology is used to measure alignment error accurately, and precision motion control is used in correcting errors nd mounting FPC. The two picker heads handling two FPC together is used to increase the productivity.

• Journal of Institute of Convergence Technology
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• v.3 no.2
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• pp.31-37
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• 2013

This paper proposes a vision-based inspection algorithm for a punch which is used when forming the head of the small screws. To maintain good quality of punch, the precise inspection of its dimension and the depth of the punch head is important. A CCD camera and an illumination dome light are used to measure its dimensions. And a structured line laser is also used to measure the depth of the punch head. Resolution and visible area depend on setup between laser and camera which is determined using CAD-based simulation. The proposed method is successfully evaluated using experiment on #2 punch.

• Journal of the Semiconductor & Display Technology
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• v.9 no.3
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• pp.59-63
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• 2010

This paper proposes computer visual inspection algorithms for various LCD defects which are found in a manufacturing process. Modular vision processing steps are required in order to detect different types of LCD defects. Those key modules include RGB filtering for pixel defects, gray-scale morphological processing and Hough transform for line defects, and adaptive threshold for spot defects. The proposed algorithms can give users detailed information on the type of defects in the LCD panel, the size of defect, and its location. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.2
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• pp.94-103
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• 2004

The vision system model used for this study involves the six parameters that permits a kind of adaptability in that relationship between the camera space location of manipulable visual cues and the vector of robot joint coordinates is estimated in real time. Also this vision control method requires the number of cameras to transform 2-D camera plane from 3-D physical space, and be used irrespective of location of cameras, if visual cues are displayed in the same camera plane. Thus, this study is to investigate the optimal number of cameras used for the developed vision control system according to the change of the number of cameras. This study is processed in the two ways : a) effectiveness of vision system model b) optimal number of cameras. These results show the evidence of the adaptability of the developed vision control method using the optimal number of cameras.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.209-212
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• 2018

Anisotropic conductive film(ACF) bonding is widely used for making fine interconnections between two different materials where soldering is not easily applicable. There are three constraints for the successful implementation of ACF bonding. A bonding contact should be pressed by a hot head with the right pressure and temperature for a pre-defined curing time. In this paper, a method for ACF bonding based on machine vision system is proposed and verified through some experiments. The system calculates the position and orientation of printed circuit boards(PCBs) on a bonding table and estimates the optimal hitting point where the hot head should be applied. Experimental results show that the proposed system achieves better adhesive strength by providing head flatness over contact surfaces.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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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.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1997.06c
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• pp.238-246
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• 1997

This study was conducted to develop a robotic transplanter for bedding plants. The robotic transplanter consisted of machine vision system, a manipulator, a gripper and plug tray transfer system. The performance of the robotic transplanter was tested and compared by two different transplanting methods, which were to consider the leaf orientation of seedlings and not to. Results of this study were as follows. (1) A cartesian coordinate manipulator for a robotic transplanter with 3 degree of freedom was constructed. The accuracy of position control was $\pm$1 mm. (2) The robotic transplanter with the machine vision system, the manipulator, the gripper and the transfer system was developed and tested with a shovel-type finger. Without considering the orientation of leaves, the success rates of transplanting healthy cucumber seedlings in 72-cell and 128-cell plug-trays were 95.5% and 94.5% respectively. Considering the orientation of leaves, the success rates of transplanting healthy cucumber seedling in 72-cell and 128-cell plug-trays were 96.0% and 95.0% respectively.