• Korean Management Science Review
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• v.16 no.2
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• pp.79-92
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• 1999

This paper presents an automated visual inspection/measuring system for the door inner panel manufacturing process. The main objective of this research is to develop inspection applications with a machine vision system related to the determination or quantification of parameters such as dimension, shape, quality of surfaces, number of holes in a panel, and presence or absence of specific features. For quality measurements, we showed a subpixel image processing technology that will improve the consistency of results and level of precision. Also presented is a data analysis method th detect process shifts so that corrective action can be undertaken before more defective units are manufactured.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.125-130
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• 2016

Automatic quality inspection by computer vision can be applied and give a solution to the pharmaceutical industry field. Pharmaceutical capsule can be easily affected by flaws like dents, cracks, holes, etc. In order to solve the quality inspection problem, it is required computationally efficient image processing technique like thresholding, boundary edge detection and segmentation and some automated systems are available but they are very expensive to use. In this paper, we have developed a dented capsule image processing technique using edge-based image segmentation, TLS(Total Least Squares) curve fitting technique and adopted low cost camera module for capsule image capturing. We have tested and evaluated the accuracy, training and testing time of the classification recognition algorithms like PCA(Principal Component Analysis), ICA(Independent Component Analysis) and SVM(Support Vector Machine) to show the performance. With the result, PCA, ICA has low accuracy, but SVM has good accuracy to use for classifying the dented capsule.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2738-2740
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• 2001

This paper describes a study on implementation of image processing systems for the defect inspection of polyethylene. In order to detect the edge, the Robert filter is used. And we use to the labeling algorithm for feature extraction. Labeling the conected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. This algorithm is designed for the defect inspection of polyethylene.

• Preventive Nutrition and Food Science
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• v.2 no.3
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• pp.269-279
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• 1997

Various nondestructive technologies for quality inspection of fruits and vegetables were reviewed through published literatures and selected agricultural databases. These technologies were grouped into nine categories, including acoustic response, dielectric response, machine vision, magnetic response, mechanical vibration response, microwave response, optical properties, and other possible sensing technologies. Their principles and characteristics were investigated and these technologies were presented with their current and potential applications. The link of appropriate nondestructive technologies with common principal quality parameters of fruits and vegetables was summarized.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.24-29
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• 1996

The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.451-458
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• 2004

A leather quality inspection by naked eyes has known as unreliable because of its biological characteristics like accumulated fatigue caused from an optical illusion and biological phenomenon. Therefore it is necessary to automate the leather quality inspection by computer vision technique. In this paper, we present automatic leather qua1ity classification system get information from leather surface. Leather is usually graded by its information such as texture density, types and distribution of defects. The presented algorithm explain how we analyze leather information like texture density and defects from the gray-level images obtained by digital camera. The density data is computed by its ratio of distribution area, width, and height of Fourier spectrum magnitude. And the defect information of leather surface can be obtained by histogram distribution of pixels which is Windowed from preprocessed images. The information for entire leather could be a standard for grading leather quality. The proposed leather inspection system using machine vision can also be applied to another field to substitute human eye inspection.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.1-6
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• 2010

The lens distortion in the machine vision system is inevitable phenomenon. Distortion is getting worse, due to the selection of lens in the trend of reducing prices and size of the system. In this trend, the distortion correction becomes more important. But, the traditional correction methods has problems, such as complexity and requiring more operations. Effective distorted digital image correction is the precondition of target detection and recognition based on vision inspection. To overcome the disadvantage of traditional distortion correction algorithms, such as complex modeling, massive computation and marginal information loss, an image distortion correction algorithm based on photogrammetry method is proposed in this paper. In our method, we use the lattice image as the measurement target. Through the experimental results, we could find that we can reduce the processing time by 4ms. And also the inspection failure rate of our method was reduced by 2.3% than human-eyes inspection method.

• Design & Manufacturing
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• v.14 no.1
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• pp.8-14
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• 2020

In general, auto parts production assembly line is assembled and produced by automatic mounting by an automated robot. In such a production site, quality problems such as misalignment of parts (doors, trunks, roofs, etc.) to be assembled with the vehicle body or collision between assembly robots and components are often caused. In order to solve such a problem, the quality of parts is manually inspected by using mechanical jig devices outside the automated production line. Automotive inspection technology is the most commonly used field of vision, which includes surface inspection such as mounting hole spacing and defect detection, body panel dents and bends. It is used for guiding, providing location information to the robot controller to adjust the robot's path to improve process productivity and manufacturing flexibility. The most difficult weighing and measuring technology is to calibrate the surface analysis and position and characteristics between parts by storing images of the part to be measured that enters the camera's field of view mounted on the side or top of the part. The problem of the machine vision device applied to the automobile production line is that the lighting conditions inside the factory are severely changed due to various weather changes such as morning-evening, rainy days and sunny days through the exterior window of the assembly production plant. In addition, since the material of the vehicle body parts is a steel sheet, the reflection of light is very severe, which causes a problem in that the quality of the captured image is greatly changed even with a small light change. In this study, the distance between the car body and the door part and the door are acquired by the measuring device combining the laser slit light source and the LED pattern light source. The result is transferred to the joint robot for assembling parts at the optimum position between parts, and the assembly is done at the optimal position by changing the angle and step.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.5
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• pp.135-143
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• 2000

The vision system is easy to use the exclusive use as a independent computer system but it is not much popularization by reason of expensive and difficult to adapt to the various fields, because it is easy to the existed computer system, the price is cheap and also it can use to the various measurement purpose which user wanted and programed. The measurement method of the vehicle axle casing nut welding part is that measure the value of the welding part to adapt the actual operation program from using the ratio between the actual length of the standard specimen and the length of image, to measure the ratio between the actual product and the camera image. A defect is found by the assembled visual inspection system. The inspection algorithm which estimates the quality of welded product is developed and also, the software program which processes the automatic test function of the inspection system. We make the foundation of the inspection automatic system and we will help to apply other welding machine.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1720-1721
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• 2008

인간에게 있어서 시각 능력이란 정보 취득 및 처리 과정에 있어서 중요한 역할을 한다. 이러한 능력은 기계에 있어서도 자동화가 진전이 될수록 기계의 시각 능력 즉, 머신 비전의 기술이 중요한 역할을 한다. 따라서 산업이 발전함에 따라 머신 비전의 기술은 여러 분야에 걸쳐 요구되며, 이에 따른 연구가 활발히 진행되고 있다. 본 연구에서도 산업 현장에 적용 할 수 있는 최적의 머신 비전 시스템 설계를 목적으로 하였으며, 그에 따른 PCB기판 검사 시스템에 대하여 연구하였다.