• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.117-120
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• 1996

In this paper, a new approach to acquire the cross-sentional image for automatic solder joint inspection of double-sided PCB using X-ray source is presented. We designed the apparatus with fixed X-ray source to realize the cross-sectional image by tunning object and detector synchronously. The cross-sectional images are captured at several view angle of X-ray source, the geometric image distortions caused by view angle and the shape of image intensifier are compensated. The precision variation of cross-sectional image by the change of view angle was investigated. Also we acquired the cross-sectional image to the solder joint of double-sided PCB and reconstructed the shape of solder joint.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1737-1742
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• 2015

In the industrial field for product inspection needs not only on the surface of the product but also the internal components defect inspection. Generally, optical inspection is mainly used for item inspection from production process. However, this is only to check defect of surface it is difficult to perform inspection of goods internal. To overcome these limitations, Instead of optical device by using the portable X- ray DR image acquisition device system developed to obtain an image in real time at the same time and determine product defects. After obtaining the X- ray image, the inspection product within error range is passed after machine image processing. Also, the results and numbers are stored by users.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.794-800
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• 2015

This paper describes the design for a defective product inspection device for the curved glass used in smart-phone. Cameras are used as inspection devices to find cracks in LCDs (Liquid Crystal Displays), PDPs (Plasma Display Panels), etc. The devices used to inspect the curved glass used in smart-phone consist of a camera, two back-light apparatus, an inspection apparatus main body, and an image processing program. Camera image calibration was performed to smooth an image taken with the camera, and as a result, the average error was less than 0.12 pixels. And the image of a smart-phone's curved glass taken with the camera was processed using the produced program. As a result, the program could correctly extract the cracks on the curved glass. Thus, it is thought that the designed inspection device can successful detect cracks in curved tempered glass.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.126-134
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• 1997

In this study, We made visual inspection system using Vision Board. It is consist of an illuminator (a fluorescent lamp), image input device (CCD (Charge-Coupled Device) camera), image processing system(Vision Board(FARAMVB-02)), image output device (video monitor, printer), and a measuring instrument(TELMN1000). Length measurement by visual inspection system make use of 100mm guage block(instead of calculating distance between a camera and a object). It measured horizontal and vertical length factor from 400mm to 650mm by increasing 50mm. In this place, measured horizontal and vertical length factor made use of length measure- ment of a injection. A measuring instrument used to ompare a measured length of a injection visual inspection system with it. In conclusion, length measurement of a injection compared a measuring instrument with visual inspecion system using length factor of 100mm gauge block. We find that maximum error of length is 0.55mm when it compar with the measuring value of two devices(FARAMVB-02, TELMN1000). Program of visual inspection system is made up Borland C++3.1.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.569-571
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• 2010

In this paper, we develop a vision inspection system for inspecting flaws on plastic products such as insufficient moldings, spots, scratches. The inspection algorithm for this system consist of image binarization for curved structure of plastic products, image noise removal using morphology operation, labeling methods for candidate regions and image filtering and calibration method for flaw inspection. In order to improve its performance, we also develop fast image processing algorithm based on GUI. To verify the effectiveness of this system, we conducted evaluation for the system accuracy and the inspection algorithm processing time.

• Journal of the Semiconductor & Display Technology
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• v.17 no.1
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• pp.27-34
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• 2018

Industrially, die-casting products are formed through casting, and so the methods to inspect the defects inside them are very restrictive. External inspection methods including visual inspection, sampling judgment, etc. enables researchers to inspect possible external defects, but x-ray inspection equipment has been generally used to inspect internal ones. Recently, they have been also applying three-dimensional internal inspections using CT equipment. However, they have their own limitations in applying to the use of industrial inspection due to limited detection size and long calculation time. To overcome the above problems, this paper has suggested a method to inspect internal defects by comparing the CAD data of the product to be inspected with the 3D data of the CT image. In this paper, we proposed a method for fast and accurate inspection in three dimensions by applying x-ray inspection to find internal defects in industrial parts such as aluminum die casting products. To show the effectiveness of the proposed method, a series of experiments have been carried out.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.637-640
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• 1999

In this Paper we show the LCD simulator for defect inspection using image processing algorithm and neural network. The defect inspection algorithm of the LCD consists of preprocessing, feature extraction and defect classification. Preprocess removes noise from LCD image, using morphology operator and neural network is used for the defect classification. Sample images with scratch, pinhole, and spot from real LCD color filter image are used. The proposed algorithms show that defect detected and classified in the ratio of 92.3% and 94.6 respectively.

• IE interfaces
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• v.9 no.1
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• pp.73-82
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• 1996

The purpose of this research is to construct real-time image acquisition system for a line-scan inspection system as a computer vision system. To construct the line-scan inspection system, many problem arise. However, problems of image acquisitions using linear CCD are practically studied in this paper. These problems are concerned to proper lighting systems, relations with handling system, camera systems, and impacts due to the noise of environment. These problems are examined separately, and proper configurations for each case are suggested to construct the line-scan image acquisition system.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1156-1161
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• 2006

This paper describes a fast image labeling algorithm for the feature extraction of connected components. Labeling the connected regions of a digitized image is a fundamental computation in image analysis and machine vision, with a large number of application that can be found in various literature. This algorithm is designed for the surface defect inspection of Cold Mill Strip. The labeling algorithm permits to separate all of the connected components appearing on the Cold Mill Strip.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.789-792
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• 2003

Pipe inspection has a great importance to ensure safety for the nuclear power plant. In this paper, we designed visual inspection module for the tube internal, which diameter is 15${\sim}$20mm. And we made inspection module which consisted of CCD camera and light. And the relation between image and real world coordinate is established. Image processing is performed to calculate mapping parameter and analyze the size of defect. For the calculation of mapping parameter, experiment is performed using grid type test pattern. Acquired image is processed to extract image coordinate. Edge detection, thresholding, median filtering and morphology filtering is applied to extract grid pattern. Extracted image coordinate is used to calculate image to real world mapping. Lens distortion was considered and corrected to get exact data. Coordinate transformation data is provided for the users to recognize easily. Experiment was performed using grid type test pattern, we extracted lens distortion parameter and real coordinate of defect point. Radial distortion of lens was corrected but tangential distortion was not considered. As continuum to this study, the tangential distortion of lens is considered and improvement of analy zing technique for the tube internal be explored continuously.