• Journal of the Microelectronics and Packaging Society
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• v.28 no.4
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• pp.19-23
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• 2021

A statistical approach to inspection of the 3-D shape of micro solder balls is proposed, where an optical method with spatially arranged LED and specular reflection is used. The reflected image captured by a vision system was analyzed to calculate the relative displacements of LED's in the image. Also, the statistics of displacements for the solder balls contained in a captured image are used to detect existing defects, and the usefulness of the proposed method is shown via experiments.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.257-263
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• 2018

The purpose of this study is to develop an automatic inspection system for a part of the differential drive gear into the transmission. This technology will make using the microvision automatic test equipment and automatic test equipment microlaser. This is that the operator intends to make the defect rate 0 in the inspection stage of the product which has been carelessly processed. The equipment developed in this research project will be applied to many areas. Packaging companies, nut bolt processing company, precisely supplier for printing on top of the semiconductor, SMT, etc. The company wants to sell the vision inspection equipment for various applications. If the defective rate of 0 is achieved through this research project, it is also possible to secure a stable supply from the parent company, and to lay the foundations for exporting based on product reliability. When the automatic inspection system is applied to domestic automobile parts processing companies, the reliability of automobiles in Korea will be greatly increased.

• The Magazine of the IEIE
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• v.24 no.10
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• pp.23-44
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• 1997

이 글에서는 요즘 신문이나 텔레비전을 통해서 인체 내부를 돌며 검사 및 치료를 하는 마이크로 로보트 등의 차세대 첨단기술로서 일반 국민들에게 소개되기도 하며, MEMS, 마이크로머신, 마이크로시스템, 혹은 초소형 정밀기계 등으로 불리는 기술과 이 기술에 대한 각국 (미국, 일본, 유럽, 한국)의 기술 동향을 소개한다. 이에 이어서, 현재 과기처의 선도기술개발사업 (소위 G7사업) 으로서 진행되고 있는 초소형 정밀기계 기술개발 사업에 대한 소개를 한다. 이 분야에 종사하지 않는 보통 사람들을 위해 가급적 쉬운 말로 풀어 쓰도록 노력하였다. 이 글에서 다루고 있는 크기의 기본 단위는 마이크로미터 (천분의 일 밀리미터) 이며, 사람의 머리카락의 직경이 약 100 마이크로미터 (0.1mm) 내외이다. 초소형 기계나 초소형 부품들은 대개 이 머리카락의 직경정도이며, 머리카락속에 모터나 기어 등이 들어있다고 생각해도 크게 틀리지 않을 것이다.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.67-74
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• 2001

According as the patterns of PCB (Printed Circuit Board) become denser and complicated, quality and accuracy of PCB influence the performance of final product. It's attempted to obtain trust of 100% about all of parts. Because human inspection in mass-production manufacturing facilities are both time-consuming and very expensive, the automation of visual inspection has been attempted for many years. Thus, automatic visual inspection of PCB is required. In this paper, we used an algorithm which compares the reference PCB patterns and the input PCB patterns are separated an object and a scene by filtering and edge detection. And than compare two image using pattern matching algorithm. We suggest an defect inspection algorithm in PCB pattern, to be satisfied low cost, high speed, high performance and flexibility on the basis of $640{\times}480$ binary pattern.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.6
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• pp.867-875
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• 2004

In order to inspect burr geometry and hole quality in micro-drilling processes, a cost-effective method using an image processing and shape from focus (SFF) methods on the machine tool is proposed. A CCD camera with a zoom lens and a novel illumination unit is used in this paper. Since the on-machine vision unit is incorporated with the CNC function of the machine tool, direct measurement and condition monitoring of micro-drilling processes are conducted between drilling processes on the machine tool. Stainless steel and hardened tool steel are used as specimens, as well as twist drills made of carbide are used in experiments. Validity of the developed system is confirmed through experiments.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.253-255
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• 2007

The increasing requirement for consistency and quality in the automotive industry started the development of a Machine Vision Inspection System (MVIS) for a car seat bottom cushion frame with the goal of providing a higher precision Inspection System with minimal components and less human intervention. The modifications made to an existing PC-based MVIS were shown to improve the accuracy and precision of the system. By using four monochrome cameras, the working distance was lowered and the image distortions were lessened without resorting to extensive image processing. The inspection scripts were evaluated if it could recognize good and bad products and were shown to be robust and able to reach an acceptable level of precision. It was also shown that the amount of human interaction was lessened.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.389-390
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• 2006

The goal of this paper is automation of a remocon inspection process using machine vision system. This system prevents error that is occurred by physical and spirit condition of human. Also this system has been developed to raise the reliability of remocon inspection. This system has been developed only using PC, CCD Camera and Visual C++ for universal workplaces. The performance of this system is an accuracy improvement of $2{\sim}3[%]$ and a processing time reduction of about 100[ms] against existing pattern matching method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.181-189
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• 2023

In this paper, we present a case study of developing MVIS (Machine Vision Inspection System) designed for exterior quality inspection of stamping dies used in the production of automotive exterior components in a small to medium-sized factory. While the primary processes within the factory, including machining, transportation, and loading, have been automated using PLCs, CNC machines, and robots, the final quality inspection process still relies on manual labor. We implement the MVIS with general-purpose industrial cameras and Python-based open-source libraries and frameworks for rapid and low-cost development. The MVIS can play a major role on improving throughput and lead time of stamping dies. Furthermore, the processed inspection images can be leveraged for future process monitoring and improvement by applying deep learning techniques.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.784-793
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• 2012

Defects of TFT-LCD is detected by thresholding the difference image between the input image and template one because LCD panel has its inherent patterns. However, the pitch corresponding to pattern period is gradually changed according to the distance from the center of camera due to geometric distortion of camera characteristics. This paper presents a method to detect defects through comparing the pitch area with neighbor pitch areas where the perspective transform is performed with the extracted features to correct the distortion. The experimental results show that the performance of the proposed method is very effective for real data.

• Journal of Practical Engineering Education
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• v.6 no.1
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• pp.37-42
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• 2014

The automated visual inspection system (machine vision system) for quality assurance is important factory automation equipment in the manufacturing industries, such as display, semiconductor, etc. There is a lot of demand for the machine vision engineers. However, there are no technical training courses for machine vision technologies in vocational schools, colleges and universities. In this paper, we present the implementation of line scan camera based equipment for technical training of the automated visual inspection system. The training system consists of the X-Y stage which is widely used in machine vision industries and its variable image resolution are set to $10-30{\mu}m$. Additionally, this training system can attach the industrial illumination, either the direct illuminator or coaxial illuminator, for verifying the effect of illuminations. This means that the trainee can have a practical training in various equipment conditions and the training system is similar to the automated visual inspection system in industries.