• Journal of Korea Society of Industrial Information Systems
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• v.4 no.3
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• pp.71-78
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• 1999

This paper presents an integrated and automated inspection system using image processing technology for the automotive engine assembly process. The system make it possible for the inspected data to be entered directly from the machine vision into the statistical process control system. Such direct entry enables the prompt preparation of corrective actions against process problems. An IVP-150 machine vision board is installed within the PC for image processing, and a template matching technology is implemented to precisely verify quality factors. The developed system showed robustness to the problems of noise, distortion, and orientation.

• International Journal of Quality Innovation
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• v.4 no.2
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• pp.50-64
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• 2003

During IC inspection, which includes the two parts of Mark and Lead, the deviation of IC on the tape occurring in high speed movements usually generates light reflection effect, which in turn causes errors in IC recognition as measured by machine vision system. This research filters the light reflection effect by developing standard components, identifies the correct position of IC Lead, hence fixes the measurement errors or non-measurability caused by light reflection, avoids the resulting discontinued operation of measuring system, and improves the productivity.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.53-58
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• 2017

Recently, advance in technology have increased the importance of visual inspection in semiconductor inspection areas. In PCB visual inspection, accurate line estimation is critical to the accuracy of the entire process, since it is utilized in preprocessing steps such as calibration and alignment. We propose a line estimation method that is differently weighted for the line candidates using a histogram of gradient information, when the position of the initial approximate corner points is known. Using the obtained line equation of the outline, corner points can be calculated accurately. The proposed method is compared with the existing method in terms of the accuracy of the detected corner points. The proposed method accurately detects corner points even when the existing method fails. For high-resolution frames of 3.5mega-pixels, the proposed method is performed in 89.01ms.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1218-1230
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• 2019

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.2
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• pp.92-99
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• 2007

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding systems, is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. In this paper, novel presented, developed vision processing techniques are detailed, and their application in welding fabrication is covered. The software for joint tracking system is finally proposed.

• 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.

• 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.

• 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.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.212-220
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• 2024

A recently the advancement of society, AI technology has made significant strides, especially in the fields of computer vision and voice recognition. This study introduces a system that leverages these technologies to recognize users through a camera and relay commands within a vehicle based on voice commands. The system uses the YOLO (You Only Look Once) machine learning algorithm, widely used for object and entity recognition, to identify specific users. For voice command recognition, a machine learning model based on spectrogram voice analysis is employed to identify specific commands. This design aims to enhance security and convenience by preventing unauthorized access to vehicles and IoT devices by anyone other than registered users. We converts camera input data into YOLO system inputs to determine if it is a person, Additionally, it collects voice data through a microphone embedded in the device or computer, converting it into time-domain spectrogram data to be used as input for the voice recognition machine learning system. The input camera image data and voice data undergo inference tasks through pre-trained models, enabling the recognition of simple commands within a limited space based on the inference results. This study demonstrates the feasibility of constructing a device management system within a confined space that enhances security and user convenience through a simple real-time system model. Finally our work aims to provide practical solutions in various application fields, such as smart homes and autonomous vehicles.

• Transactions of the KSME C: Technology and Education
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• v.5 no.1
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• pp.63-67
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• 2017

Nobody deny that Machine Tool has leaded to the development of mechanical technology as it is known for long time. According to this, it has always been changed newly by appling advanced technology. This paper introduces the evolution history of machine tools and describes how the ICT is applied to develop a new type of machine tool. For that, it has been shown what kind of elementary technologies are required. The future vision has also been concluded in this paper.