• 대한임베디드공학회논문지
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• 제17권3호
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• pp.177-183
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• 2022

To measure the size and weight of the fish, we developed an automatic fish size measurement system using a deep neural network, where the YOLO (You Only Look Once)v3 model was used. To detect fish, an IP camera with infrared function was installed over the fish pool to acquire image data and used as input data for the deep neural network. Using the bounding box information generated as a result of detecting the fish and the structure for which the actual length is known, the size of the fish can be obtained. A GUI (Graphical User Interface) program was implemented using LabVIEW and RTSP (Real-Time Streaming protocol). The automatic fish size measurement system shows the results and stores them in a database for future work.

• 반도체디스플레이기술학회지
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• 제14권1호
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• pp.7-11
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• 2015

In this paper, an automatic focusing method has been proposed for speedy and reliable measurement and inspection in industry. It is very difficult to determine focusing step size and moving direction in one camera autofocusing. The proposed method can improve speed and accuracy of focusing by using the optical axis interval of two cameras, which is automatically set up as focusing step size. Also, it can determine moving direction from focus value comparisons of two cameras, and then solve ambiguity of one camera focusing. Its performance is verified by experiments. It is expected that it can apply to optical system for measurement and inspection in industry fields.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.1230-1242
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• 1993

In a case of mushroom (Lentinus Edodes L.) , visual features are crucial for grading and the quantitative evaluation of the growth state. The extracted quantitative visual features can be used as a performance index for the drying process control or used for the automatic sorting and grading task. First, primary external features of the front and back sides of mushroom were analyzed. And computer vision based algorithm were developed for the extraction and measurement of those features. An automatic thresholding algorithm , which is the combined type of the window extension and maximum depth finding was developed. Freeman's chain coding was modified by gradually expanding the mask size from 3X3 to 9X9 to preserve the boundary connectivity. According to the side of mushroom determined from the automatic recognition algorithm size thickness, overall shape, and skin texture such as pattern, color (lightness) ,membrane state, and crack were quantified and measured. A portion of t e stalk was also identified and automatically removed , while reconstructing a new boundary using the Overhauser curve formulation . Algorithms applied and developed were coded using MS_C language Ver, 6.0, PC VISION Plus library functions, and VGA graphic function as a menu driven way.

• 반도체디스플레이기술학회지
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• 제13권1호
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• pp.51-55
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• 2014

In this paper, an hybrid automatic focusing method has been proposed for speedy and reliable measurement and inspection in industry. It can improve reliability of focusing position by using not a focusing measure but the hybrid one that is incorporated with sobel operator and auto-correlation. Also, it can not only reduce control time of focusing position using adaptive step size, but also improve accuracy of focusing position by gaussian interpolation. Its performance is verified by experiments. It is expected that it can apply to optical system for measurement and inspection in industry fields.

• 한국의상디자인학회지
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• 제14권1호
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• pp.81-96
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• 2012

The purpose of this study is to provide fundamental information for standardization of 3D body measurement. This research analyzes errors occurring in the process of extracting body size from 3D body scan data. First, as a result of analyzing basic state of the 3D body scanner's calibration, the point number of each section was almost the same, while the right and left as well as the front and back coordinates of the center of gravity are not, showing unstable data. Nevertheless, the latter does not influence on the size of cylinder such as width and circumference. Next, we analyzed point coordinates variations of scan data on a mannequin nude by life casting. The result was great deflection in case of complicated or horizontal sections including the reference point beyond proper distance from centers of four cameras. In case of the mannequin's size, accuracy proves comparatively high in that measurement errors in height, width, depth, and length dimension occurred all within allowable errors, only except chest depth, while there were a lot of measurement errors in a circumference dimension. Secondly, analysis of accuracy of automatic extraction identification program algorithm presented that a semi-automatic measurement program is better than an automatic measurement program. While both of them ate very acute in parts related to crotch, they are not in armpit related parts. Therefore, in extracting of human body size from 3D scan data, what really matters seems to parts related to armpits.

• 전자공학회논문지SC
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• 제41권5호
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• pp.1-8
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• 2004

본 논문에서는 개인용 컴퓨터와 CCD 카메라를 이용하여 실시간처리에 의해 생산 공정에서 자동으로 경량기포 콘크리트 블록의 각종 치수 측정을 할 수 있는 시스템 설계방법을 제안하였다. 또한 제안한 치수측정 자동화 알고리즘은 실제 작업환경을 고려하여 이중에지를 고려한 경계결정방법, 작업공정내의 피사체의 진동을 고려한 단위길이 결정방법, 카메라의 곡률보정에 의한 치수오차 보정 방법 등을 적용함으로써, 고성능의 하드웨어 장비를 이용하지 않고서도 실제공정에서의 실험결과를 통해 모든 경량기포 콘크리트 블록의 치수에 대해 1mm이내의 오차를 보장하므로, 설계한 시스템이 적합한 치수측정 시스템임을 확인할 수 있었다.

• 제어로봇시스템학회논문지
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• 제19권11호
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• pp.974-978
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• 2013

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on the same defect with some variations on position or rotation mainly because different images are provided. This is caused by possible variations from the image acquisition process including optical factors, nonuniform illumination, random noises, and so on. For this reason, conventional area based defect measuring methods have problems of robustness and consistency. In this paper, we propose a new defect size measuring method to overcome this problem, utilizing volume information that is completely ignored in the area based defect measuring method. The results show that our proposed method dramatically improves the robustness and consistency of defect size measurement.

• 문화기술의 융합
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• 제9권1호
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• pp.347-353
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• 2023

현재 軍(육군) 입대 장병은 신병훈련소에서 신체에 대한 치수 측정(자동, 수동) 및 샘플 피복을 착용해 본 후, 희망하는 치수로 피복을 지급받고 있다. 하지만, 민간 평상복보다 상대적으로 매우 세분화된 치수 체계를 적용하고 있는 軍에서는 이와 같은 치수 측정 과정에서 발생하는 측정된 치수의 낮은 정확도로 인해 지급받은 피복이 제대로 맞지 않아 피복을 교체하는 빈도가 매우 빈번히 발생하고 있다. 뿐만 아니라 서구적으로 변화된 MZ 세대의 체형변화를 반영하지 않고, 10여 년 전(前)에 수집된 구세대 체형 데이터 기반의 치수 체계를 적용함으로써 재고량이 비효율적으로 관리되는 문제점이 있다. 즉, 필요한 규격의 피복은 부족하고 불필요한 규격의 피복재고는 다수 발생하고 있다. 따라서, 피복 교체빈도를 감소시키고 재고관리의 효율성을 향상하기 위해 딥러닝 기반의 신체 치수 자동측정과 빅데이터 분석 및 머신러닝 기반의 "입대 장병 개인 맞춤형 피복 자동 추천 시스템"을 제안한다.

• 패션비즈니스
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• 제16권1호
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• pp.150-159
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• 2012

This study intend to analyze differences between 3D body scanning sizes and direct measurement sizes of same subjects. The subjects of study are female students of university in China. 3D data analyze as a 3D Body Measurement Soft System. The conclusion found is as below: In case of circumferences, error between direct-measurement size and 3D body scanning size is from 4.9mm to 62.2mm. The neck circumference size of directmeasurement is bigger than 3D body scanning size. The height error range is from 0.6mm to 51mm. Height of underbust, waist and hip are that direct-measurement sizes are higher than 3D body scanning sizes. Gap of width is from 3.8mm to 21.9mm. The gap range is too narrow relatively to others. Only direct-measurement size of neck width is wider than 3D body scanning size. Error range of length is from 0.3mm to 41.8mm. 3D body scanning sizes of lateral neck to waistline, upperarm length, arm length, neck shoulder point to breast point, shoulder center point to breast point, lateral shoulder to breast point are longer than direct-measurement sizes. They have a negative margin of error. I intend to set up same measurement point between direct-measurement and 3D body scanning but they have some errors because direct-measurement point is applied by a person. 3D body scanning measurement point is settled by automatic system. A measurement point of direct-measurement and 3D body scanning isn't unite. So we need to make a standard of setting up measurement points.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.163-165
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• 2009

Automatic Vision Inspection(AVI) systems automatically detect defect features and measure their sizes via camera vision. It is important to predict the performance of an AVI to meet customer's specification in advance. In this paper, we propose a statistical method for prediction of false alarm rate regarding inconsistency of defect size measuremet process. We only need are a simple experimental trial for repeated defect size measurement test. The statistical features from the experiement are utilized in the prediction process. Therefore, the proposed method is swift and easy to implement and use. The experiment shows a close prediction compared to manual inspection results.