• 한국산학기술학회논문지
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• 제15권6호
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• pp.3376-3382
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• 2014

전자내시경을 이용하여 양극처리된 알루미늄 실린더튜브 내면의 결함을 자동으로 검사하는 시스템을 개발하였다. 이 시스템은 크게 자동 결함검사 소프트웨어, 전자내시경 및 이송장치 등으로 구성되어 있다. 실험을 통하여 자동 결함검사의 최적검출 조건을 도출하여 실린더튜브 내면의 결함 검사에 적용한 결과 주요 결함 요소인 스크래치, 산화물, 라인, 웰드라인의 인식률을 99%로서 만족하였다. 자동 결함검사 시스템을 생산현장에 적용하면 기존의 육안 검사 시 작업자가 가지는 육체적인 피로도 줄여 작업효율을 증가시키며, 결함검출 자료를 바탕으로 제품의 품질을 향상시킬 수 있다.

• 한국정밀공학회지
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• 제16권12호
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• pp.60-70
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• 1999

An efficient automatic inspection system for Floating Seal is developed, The proposed system consists of a high resolution line scan camera, microcomputer, and PLC (Programmable Logic Controller). In order to perform rapid inspection, The ROI (Region of Interest) is extracted from the original image. There are types of defects; shape defects and surface defects. Each features of defects are captured by edge detect, segmentation, morphological operation, and threshold analysis. PLC controller is used to synchronize the whole system and store the inspection results temporarily to reduce the overhead of microcomputer. As a result, the system is being utilized successfully in a teal inspection line.

• 한국생산제조학회지
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• 제20권5호
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• pp.666-672
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• 2011

In this paper, we describes the development of automatic inspection system for detecting the defects on photovoltaic wafer by using machine vision. Until now, The defect inspection process was manually performed by operators. So these processes caused the produce of poorly-made articles and inaccuracy results. To improve the inspection accuracy, the inspection system is not only configured, but the image processing algorithm is also developed. The inspection system includes dimensional verification and pattern matching which compares a 2-D image of an object to a pattern image the method proves to be computationally efficient and accurate for real time application and we confirmed the applicability of the proposed method though the experience in a complex environment.

• 제어로봇시스템학회논문지
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• 제14권5호
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• pp.444-452
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• 2008

This paper presents an overall image processing approach of defect inspection of patterned TFT-LCD panels for the real manufacturing process. A prototype of AOI(Automatic Optical Inspection) system which is composed of air floating stage and multi line scan cameras is developed. Adjacent pattern comparison algorithm is enhanced and used for pattern elimination to extract defects in the patterned image of TFT-LCD panels. New region merging algorithm which is based on border expansion is proposed to identify defects from the pattern eliminated defect image. Experimental results show that a developed AOI system has acceptable performance and the proposed algorithm reduces environmental effects and processing time effectively for applying to the real manufacturing process.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.35.3-35
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• 2001

Developed is an optical auto-inspection system to detect some microscopic defects on the Inside surface of the hydraulic automobile brakes at the production line. A small cylindrical detection module with a solid laser source at its center has two rings of optical fibers to separately collect light reflected and scattered from the defects on the surface. The cylindrical brake part rotates with respect to the detection module that will move parallel to the rotational axis of the cylinder. Thus, the optical module can scan the whole inside surface area. The automatic detection of the defects is to compare the intensity distributions ...

• 정보처리학회논문지B
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• 제10B권3호
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• pp.305-310
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• 2003

본 논문은 자동으로 볼트를 고속 정밀 검사할 수 있는 장치에 대한 시스템 설계 및 제품 개발에 관해 다룬다. 볼트를 연속적으로 고속 검사하기 위해 컨베이어를 이용하고 이를 동작시키기 위한 서보모터와 엔코더를 부착하여 정확한 이송량를 유지하게 된다. 엔코더 신호를 수신한 라인스캔 카메라의 동작에 따라 프레임 그래버로 볼트 영상을 전송하며 한 프레임을 구성한 후 영상 검사 알고리즘에 의해 파라메터를 측정하고 검사하게 된다. 제작된 결과물을 이용하여 실험을 통해 본 장치의 효용성을 입증하고자 한다.

• 한국기계가공학회지
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• 제21권6호
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• pp.22-29
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• 2022

In this study, an automatic marking system for fabric inspection machines was developed. The main objectives of the study were to promote intelligence and automation for the inspection process, as well as to increase textile industrial productivity. Generally, when a worker manually inspects and marks a fabric, human error and reduced efficiency are unavoidable. To overcome these problems, we developed an automatic marking system that uses robots. This system incorporates a vision camera to automatically recognize defects, and an optical fiber sensor to detect the side of the fabric. To verify the performance, the control system sends a command directly to the robot to mark the fabric. Finally, the actual production confirmed that the proposed system could perform the desired motion.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.959-962
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• 1988

This paper describes an automatic visual inspection system for fabric defects based on pattern recognition techniques. The inspection for fabric defects can be separated into three sequences of operations which are the detection of fabric defects[1], the classification of figures of fabric defects, and the classification of fabric defects. Comparing projections of defect-detected images with the predefined complex, the classification accuracy of figures of fabric defects was found to be 95.3 percent. Employing the Bayes classifier using cluster shade in SGLDM and variance in decorrelation method as features, the classification accuracy of regional figure defects was found to be 82.4 percent. Finally, some experimental results for line and dispersed figures of fabric defects are included.

• 스마트미디어저널
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• 제11권9호
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• pp.47-55
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• 2022

스마트팩토리 제조공정에서의 품질관리는 중요한 요소이다. 현재, 금형 공정으로 생산되는 생활가전 제조부품의 품질검사는 대부분 작업자의 육안으로 진행되고 있으며 이로 인한 검사의 오류율이 높은 실정이다. 이러한 품질공전 개선을 위하여 결함 자동검출 시스템을 설계하여 구현하였다. 제안 시스템은 특정 위치에서 고성능 스캔 카메라로 대상물을 촬영하여 영상을 획득하고, 비전검사 알고리즘에 따라 긁힘, 찍힘, 이물질에 의한 불량품을 판독한다. 본 연구에서는 긁힘에 대한 불량 인식율을 높이기 위하여 깊이 정보 기반 분기 판단 알고리즘(Depth-based branch decision algorithm, DBD)을 개발하여 정확도를 높였다.

• 제어로봇시스템학회논문지
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• 제14권5호
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• pp.438-443
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• 2008

In this paper, segmenting and classifying low contrast defects on flat panel display is one of the key problems for automatic inspection system in practice. Problems become more complicated when the quality of acquired image is degraded by the illumination irregularity. Many algorithms are developed and implemented successfully for the defects segmentation. However, vision algorithms are inherently prone to be dependent on parameters to be set manually. In this paper, one morphological segmentation algorithm is chosen and a technique using frequency domain analysis of input images is developed for automatically selection the morphological parameter. An extensive statistical performance analysis is performed to compare the developed algorithms.