• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.6
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• pp.988-994
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• 2017

The risk of facilities in catenary is increasing because the railway section extension and high-speed train service. And visual check of workforce is not enough time to maintain the extensive railway facilities. Accordingly, The technical development trend of maintenance of railway facilities can be seen by automation and application of IT technology, especially the mechanization work and the information technology are spreading in the maintenance work of the train line solved by manpower. In this paper, we describe the method by obtaining the cantilever image using acquisition device and pole inspection system in high speed vehicle, to check the variation of the cantilever component using image processing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.191-195
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• 2003

The formation degree of sustain (ITO pattern) decides quality of PDP (plasma display panel). For this reason. it makes efforts in search defects more than 30 ${\mu}{\textrm}{m}$. Now, the existing inspection process is dependent upon naked eye or SEM equipment in off-line PDP manufacturing process. In this study developed prototype inspection system of PDP ITO glass. This system creates information that detects and sorts kind of defect automatically. Design ed inspection technology adopts line-scan method by slip-beam formation for the minimum of inspection time and image processing algorithm is embodied in detection ability of developed system. Designed algorithm had to make good use of kernel matrix which draws up an approach to geometry. A characteristic of area-shaped defects, as pin hole, substance, protrusion et al, are extracted from blob analysis method. Defects, as open, short, spots, et al, are distinguished by line type inspection algorithm. In experiment results, we could have ensured ability of inspection that can be detected with reliability of up to 95% in about 60 seconds

• Smart Structures and Systems
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• v.22 no.2
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• pp.209-221
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• 2018

Efflorescence is a phenomenon primarily caused by a carbonation process in concrete structures. Efflorescence can cause concrete degradation in the long term; therefore, it must be accurately assessed by proper inspection. Currently, the assessment is performed on the basis of visual inspection or image-based inspection, which may result in the subjective assessment by the inspectors. In this paper, a novel approach is proposed for the objective and quantitative assessment of concrete efflorescence using hyperspectral imaging (HSI). HSI acquires the full electromagnetic spectrum of light reflected from a material, which enables the identification of materials in the image on the basis of spectrum. Spectral angle mapper (SAM) that calculates the similarity of a test spectrum in the hyperspectral image to a reference spectrum is used to assess efflorescence, and the reference spectral profiles of efflorescence are obtained from theUSGS spectral library. Field tests were carried out in a real building and a bridge. For each experiment, efflorescence assessed by the proposed approach was compared with that assessed by image-based approach mimicking conventional visual inspection. Performance measures such as accuracy, precision, and recall were calculated to check the performance of the proposed approach. Performance-related issues are discussed for further enhancement of the proposed approach.

• Smart Structures and Systems
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• v.13 no.6
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.246-254
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• 2001

In this paper, we described an approach to the automation of visual inspection of BGA solder joint defects of surface mounted components on printed circuit board by using neural network. Inherently, the BGA solder joints are located underneath its own package body, and this induces a difficulty of taking good image of the solder joints by using conventional imaging systems. To acquire the cross-sectional image of BGA sol-der joint, X-ray cross-sectional imaging method such as laminography and digital tomosynthesis has been cur-rently utilized. However, the cross-sectional image obtained by using laminography or DT methods, has inher-ent blurring effect and artifact. This problem has been a major obstacle to extract suitable features for classifi-cation. To solve this problem, a neural network based classification method is proposed int his paper. The per-formance of the proposed approach is tested on numerous samples of printed circuit boards and compared with that of human inspector. Experimental results reveal that the method provides satisfactory perform-ance and practical usefulness in BGA solder joint inspection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1157-1162
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.22-24
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• 2004

This paper proposes a printing quality inspection system of film-type envelopment. Since the printing system is running at very high-speed (140m/min.) and the line error has very narrow width, we have to choose one-dimensional high-speed and high-resolution line scan camera. The vibration of the printing machine and the illumination environment make the inspection problem more harder. To obtain reliable inspection results, many software image processing techniques are applied and many parameters are tuned. The performance of the proposed system is proved by many simulations and long time real-plant experiments.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.82-88
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• 2005

The damage inspection of container surface is performed by the expert inspectors at the container terminal gate of harbor. In this paper, we substitute the expert's capability with the damage inspection system using the artificial intelligent control algorithm and vision system, so we can improve the work environment and effectively decrease the inspection time and cost. Firstly, using six CCD cameras attached to the terminal gate, whole container is partially captured according to eleven sensors aligned with the entering direction of container. Captured partial images are inspected by the fuzzy system which the expert's technology is embedded. Next, we compose partial images to be a complete container image through the correlation coefficient method. Complete container image is saved to solve future troublesome problems. In this paper, the effectiveness of the proposed system was verified through the field test.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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• pp.406-414
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• 1997

A real-time inspection system is developed using line scan cameras. Several improved algorithms are proposed for real-time detection of defects in this automated inspection system. The major improved algorithms include the preprocessing, the threshold decision, and the clustering algorithms. The preprocessing algorithms are for exact binarization and the threshold decision algorithm is for fast detection of defects in 1-D binary images. The clustering algorithm is also developed for fast classifying of the defects. The system is applied to PCBs(Printed Circuit Boards) inspection. The typical defects in PCBs are pits, dent, wrinkle, scratch, and black spots. The results show that most defects are detected and classified successfully.