• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.23-31
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• 2003

• Korean Journal of Optics and Photonics
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• v.20 no.2
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• pp.134-140
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• 2009

In this study, the influence of surface roughness on light scattering from Au pads on a PCB surface was investigated. Angular distributions of light scattered from Au pads with different surface roughness were measured for several incident angles. Diffusely-scattered light could be separated by using the fact that the amount of specularly-scattered light was directly related to surface roughness. The separated diffuse term was curve-fitted with a physics-based model, and then the related scattering parameters were extracted and compared with measured parameters.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.97-104
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• 2010

In this paper, ICT (in circuit tester) inspection system and inspection algorithm is proposed and detects whether inferiority exists or not in the mounted device on the flexible PCB in cell phones or mobile display devices. The system is composed of PD (pin-driver) and GGM (ground guarding method). The structural characteristics of these flexible PCB are analyzed, which is needed to input or output the test signal. Test signal to investigate the characteristics of passive components is generated using modified circuit diagram and proposed inspection algorithm. PM (pin-map) is decided on the basis of circuit diagram and has the information about the kind of test signal to be applied and the pad number for the test signal to be connected. PD is designed to load a proper test signal for a specific pad and is adjusted according to PM so that the reconstructed circuit has minimum node and mash. The proposed ICT inspection system is realized using PD and GGM. Using the system, an experiment for each passive component is done to investigate the measurement accuracy of the developed system and an experiment for real flexible PCB model is done to verity the effectiveness of the system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.80-90
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• 1994

In this paper, a high-resolution algorithm for detecting the orientation and position of the SMD and an algorithm for compensating the position and skew angle of the PCB are proposed. The proposed algorithm for the first topic consists of two parts. Its first part is a preprocessing step. in which corner points of the SMD are detected and they are grouped. Then the coarse angle of the principal axis is obtained by line fitting. The second part is a main processing step, in which the fuzzy Hough transform over the limited range of angles is applied to the corner points to detect precisely the orientation of the SMD. The position of the SMD is determined by using its four corner points. The proposed algorithm for the second topic is the one which detects a rotation angle and translation parameters of the PCB using a template matching method. The computer simulation shows that the parametes obtained by proposed algorithms are more precise than those by the several conventional methods considered. The proposed algorithms can be applied to the fast and accurate automatic inspection systems.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.340-342
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• 2006

기존의 PCB 자동시각검사 시스템은 창조 비교 방법을 위한 참조 영상(골든 영상) 획득에 많은 어려움을 겪고 있다. 이러한 문제를 해결하기 위하여 본 연구에서는 PCB 제작에 사용되는 CAD 파일을 이용하여 참조 영상을 생성함으로써 학습을 좀 더 쉽고 간??하게 할 수 있는 시스템을 구현하였다.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.211-212
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• 2008

본 논문에서는 LCD 구동 모들 PCB의 기능 검사를 위한 자동 검사시스템인 EVT(Emulated Vision Tester)를 제안하고 구현하였다. 기존의 대표적인 자동검사 방법으로는 전기적 검사나 영상기반 검사방식이 있으나 전기적 검사만으로는 Timing이 주요한 변수가 되는 LED 장비에서는 검출할 수 없는 구동불량이 존재하며 영상기반 검사는 영상획득에 일관성이 결여되거나 Gray Scale의 구분이 불명확하며 검출결과의 재현성이 떨어진다. EVT 시스템은 Pattern Generator에서 인가된 입력 패턴 신호라 구동모듈을 통한 후 출력되는 디지털 신호를 직접 비교하여 패턴을 검사하고 아날로그 신호 (전압, 저항, 파형)의 이상 여부도 신속 정확하게 검사할 수 있는 H/W적인 방법이다. 높은 검출 신뢰도와 빠른 처리 속도 뿐만 아니라 간결한 시스템 구성으로 원가절감 실현 등 많은 장점을 가진다.

• IE interfaces
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• v.24 no.3
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• pp.231-240
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• 2011

Manufacturing enterprises have been doing their best endeavors to obtain competitiveness using various methodologies, such as information technology. In order to achieve competitiveness, they are adopting manufacturing execution system (MES). MES is a total management system that manages from the beginning of the production by product order until the quality inspection of the finished product. And MES is an inter-mediator for supplementation of information gap between ERP and inspection machine and equipment. This paper describes on establishment of effective strategy based on BPR methodology and implementation of MES small and medium PCB manufacturing company with multiple-types of products and mixed process flows. And then we proposed evaluation model based on balanced score card (BSC) for considering non-finance elements as well as finance elements. With evaluation model, we analyzed benefits and effects of MES.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.6-10
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• 2021

Recognition of characters printed or marked on the PCB components from images captured using cameras is an important task in PCB components inspection systems. Previous optical character recognition (OCR) of PCB components typically consists of two stages: character segmentation and classification of each segmented character. However, character segmentation often fails due to corrupted characters, low image contrast, etc. Thus, OCR without character segmentation is desirable and increasingly used via deep neural networks. Typical implementation based on deep neural nets without character segmentation includes convolutional neural network followed by recurrent neural network (RNN). However, one disadvantage of this approach is slow execution due to RNN layers. LPRNet is a segmentation-free character recognition network with excellent accuracy proved in license plate recognition. LPRNet uses a wide convolution instead of RNN, thus enabling fast inference. In this paper, LPRNet was adapted for recognizing characters printed on PCB components with fast execution and high accuracy. Initial training with synthetic images followed by fine-tuning on real text images yielded accurate recognition. This net can be further optimized on Intel CPU using OpenVINO tool kit. The optimized version of the network can be run in real-time faster than even GPU.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.382-395
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• 2021

In this study, character recognition using deep learning is performed among the various defects in the PCB, the purpose of which is to check whether the printed characters are printed correctly on top of components, or the incorrect parts are attached. Generally, character recognition may be perceived as not a difficult problem when considering MNIST, but the printed letters on the PCB component data are difficult to collect, and have very high redundancy. So if a deep learning model is trained with original data without any preprocessing, it can lead to over fitting problems. Therefore, this study aims to reduce the redundancy to the smallest dataset that can represent large amounts of data collected in limited production sites, and to create datasets through data enhancement to train a flexible deep learning model can be used in various production sites. Moreover, ResNet model verifies to determine which combination of datasets is the most effective. This study discusses how to reduce and augment data that is constantly occurring in real PCB production lines, and discusses how to select coresets to learn and apply deep learning models in real sites.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.3
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• pp.90-95
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• 2015

This study presents a method to test quite small-sized and light-weighted micro-drill bits which are used to make holes in printed circuit boards(PCB). After getting images of micro-drill bits through the high resolution microscope, we developed image processing algorithms to detect fiducial points, and then measured diverse factors of the drill-bit based on these points. We also developed the window-based inspection system to automatically discriminate normal and abnormal status. For the relative comparison of its performance, the system was compared with an existing inspection system using test images. Experimental results showed that the proposed system slightly improved performance, and also classified correctly some misjudged errors which were occurred in the existing system.