• 한국생산제조학회지
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• 제8권3호
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• pp.92-99
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• 1999

The inspection unit which is developed and used in this study, is processed the shape data from the CCD camera to seek welding bite section shape, and then calculated as a real dimension from measuring the value of each inspection item. The reason of measuring with the real in this study is came out from the image method which used for a long time, which is extricated the characteristic as the dimension of pixel by recognize pixel. The measurement method of the section shape is that we decide the thresholding value after we drew the histogram to binarizate the object. After that, we make flat the object to get rid of the noise and measure the shape of welded part through the boundarization of the object. The shape measurement is that measure the value of the welding part to adapt the actual operation program from using the ratio between the actual dimension of the standard specimen and the dimension of image, to measure the ratio between the actual product and the camera image. The inspection algorithm which estimates the quality of welded product is developed and also, the software GUI(Graphic User Interface) which processes the automatic test function of the inspection system is developed. We make the foundation of the inspection automatic system and we will help to apply other welding machine.

• 한국정보처리학회논문지
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• 제7권3호
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• pp.992-999
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• 2000

Textile dimension inspection is one of the basic issues in the textile dyeing and finishing industry. And also, it a plays an important role in the quality control of total fabric products. In this paper, we implement a real-time textile dimension inspection system which detects various real defects, defects positions of textile and the density of textiles. The proposed method consists of textile density measurement algorithms with zone-occurrence features from subband image which detect various types of real defects. The performance of the proposed method is tested with a number of real textile samples with 10 types of defects and three basic structures of textile. By the dimension inspection of textile at continuous stages in the fabrication process, it is possible to measure the density of textile up to 150m/min and to detect the defect of textile at real time within $\pm$1% error percentages. And also it can be monitored the condition of textile throughout at all the significant working process and can be improved textile quality.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(5)
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• pp.211-214
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• 2002

Under a continuous manufacturing process, two dimension inspection system causes problems as blurring effect and low resolution and requires position calibration between frames. One dimension inspection system is, therefore, being researched as a substitution. In this paper, we implement mechanism of switching memory and processing data for reasonable one dimension inspection system. Redundant weft image and noise was suggested to be reduced by new method using modified morphological process and masked erosion process. From resulting image, line data and possible error information were obtained and constructed as a structure. Finally, error detecting algorithm was performed with this data structure. Processing time of error detecting was 0.625ms per line in applied system and experiment showed 94.7% of error detecting ability. This method is 20% faster in speed and 2.7% higher in error detecting ability comparing with the present method.

• 한국멀티미디어학회논문지
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• 제3권2호
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• pp.112-120
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• 2000

본 논문에서는 섬유 제직 공정시 섬유 제품의 질에 영향을 미칠수 있는 섬유 결함, 결함의 위치 검출 뿐만 아니라 이동중인 섬유의 왜곡각 분류 및 섬유의 밀도를 측정할 수 있는 실시간 섬유 성량 검사 시스템을 구현하였다. 구현된 시스템에서는 잡음 문제와 실시간 처리를 위하여 광학적 렌즈로부터 섬유의 위사 부분만을 추출한 후 영역 교차법을 적용하여 섬유의 밀도를 측정하였으며, 획득된 위사 영상으로부터 평균 기울기와 가우시안 기울기 분류자를 사용하여 고속 이동 섬유 가공 공정시 발생할 수 있는 섬유의 왜곡각 분류를 통해 왜곡각 보정을 하였다. 또한 명암도 상관 행렬 특징자를 이용하여 섬유의 결함 검사와 겸함 위치를 추출하도록 하였다. 제안한 알고리즘을 적용하여 구현한 섬유 성량 검사 시스템은 고속 이동 섬유 가공 공정에 있어서 실시간으로 섬유의 밀도 계산과 섬유 결함 검출이 가능하며 섬유 염색, 제직 및 가공공정에 있어서 섬유의 상태를 모니터링 및 제어함으로써 고품질의 섬유 제품 생산이 가능하다.

• 한국멀티미디어학회논문지
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• 제24권9호
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• pp.1203-1210
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• 2021

In this paper, we developed the inspection system of electric vehicle pouch battery using image processing. Line scan cameras are used for acquiring the all parts of the pouch battery, and several steps of image processing for extracting significant dimensions(User Required Position) of the battery. In image processing, edge lines, node points, dimension lines, etc. were extracted using Preprocessor, Square Edge Detection, and Size Detection algorithms. This is used to measure the dimensions of the location requested by the user on the pouch battery. For verification of the inspection system, the dimensions of three pouch batteries produced in the same process were measured, and the mean and standard deviation were obtained to confirm the precision.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.909-910
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• 2013

• 제어로봇시스템학회논문지
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• 제9권10호
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• pp.822-831
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• 2003

A computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and the radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation is introduced for line detection. The dimension of inner and outer radius of pipe is calculated by the proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified and removed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.946-950
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• 2003

In this paper, a computer-vision based pipe shape inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle. by which pipes with wrong end-shape can be classified removed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.521-525
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• 2002

In this paper, a computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified removed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 춘계학술대회 논문집
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• pp.61-62
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• 2007