• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.165-171
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• 2004

Owing to small sizes and high density to the semiconductor It, it is difficult to discriminate the defects of ICs by human eyes. High precision inspection system with computer vision is essentially established for the manufacturing process due to the variety of defective parts. Especially it is difficult to implement the algorithm for the coplanarity of IC leads. Therefore in this paper, the inspection system which can detect the defects of the SOP types of ICs having 1cm${\times}$0.5cm of the chip size is implemented and evaluated it's performance. In order to optimally detect various items, some principles of geometry are theoretically presented , length measurement, pitch measurement, angle measurement, brightness of image and correcton of position. The interface circuit is designed for implementation of inspection system and connected the HANDLER. In the result, the system could detect two ICs' defects per second and confirmed the resolution of 20$\mu$m per pixel.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.41-45
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• 2006

The fabrication process of fiber placement system of carbon fiber reinforced plastic (CFRP) requires real time process control and reliable inspection to ensure quality by preventing defects such as delamination and void. Therefore, novel non-contact inspection technique is required during the non-destructive evaluation in a fiber placement system. For the inspection of delamination in CFRP, various methods to receive laser-generated ultrasound were applied by using piezoelectric transducer, air-coupled transducer, wavelet transform and scanning laser ultrasonic technique. Laser-generated ultrasound was received with a conventional piezoelectric sensor in contacting manner. Then signal characteristics due to defects were analyzed to find a factor for detecting defects. Air-coupled transducer was used for reception of laser-generated guided wave using linear slit array in order to generate high frequency guided wave. And line scan technique was used to confirm the capability of on-line application. The high frequency component of laser-generated guided wave received with piezoelectric sensor disappeared after propagating through delamination region. Nevertheless, it was failed to receive high frequency guided wave in using air-coupled transducer. The first peak of the frequency spectrum under 100kHz in the delamination region is higher than in the sound region. By using this feature, the line scanned frequency data were acquired in fully non-contact generation and reception of ultrasound. This method was proved as useful technique for detecting delamination in CFRP.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.1445-1454
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• 1995

In this study, we have developed a prototype of the automatic defects detection system for capsule inspection using the computer vision techniques. The subjects for inspection are empty hard capsules of various sizes which are made of gelatine. To inspect both sides of a capsule, 2-stage recognition is performed. Features we have used are various lengths of a capsule, area, linearity, symmetricity, head curvature and so on. Decision making is performed based on average value which is computed from 20 good capsules in training and permission bounds in factories. Most of time-consuming process for feature extraction is computed by hardware to meet the inspection speed of more than 20 capsules/sec. The main logic for control and arithmetic computation is implemented using EPLD for the sake of easy change of design and reduction in time for developement. As a result of experiment, defects on size or contour of binary images are detected over 95%. Because of dead zone in imaging system, detection ratio of defects on surface, such as bad joint, chip, speck, etc, is lower than the former case. In this case, detection ratio is 50-85%. Defects such as collet pinch and mashed cap/body seldom appear in binary image, and detection ratio is very low. So we have to process the gray-level image directly in partial region.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.444-452
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• 2008

This paper presents an overall image processing approach of defect inspection of patterned TFT-LCD panels for the real manufacturing process. A prototype of AOI(Automatic Optical Inspection) system which is composed of air floating stage and multi line scan cameras is developed. Adjacent pattern comparison algorithm is enhanced and used for pattern elimination to extract defects in the patterned image of TFT-LCD panels. New region merging algorithm which is based on border expansion is proposed to identify defects from the pattern eliminated defect image. Experimental results show that a developed AOI system has acceptable performance and the proposed algorithm reduces environmental effects and processing time effectively for applying to the real manufacturing process.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.571-582
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• 2010

Typically nondestructive inspection methods of the large gear units are applied to penetrate non-destructive inspection. Nondestructive penetrating inspection put into the small openings of the defect to penetration liquid, remove to excess penetration liquid on the surface of the gear units, spread with developing solution and we can find the small defect by coating with penetration liquid. However, this method has so many issues because of penetrate nondestructive tests on the gear assembly. The steep angle of screw is hard to achieved full penetration and has the problem to remove the excess. In contrast, the magnetic nondestructive inspection is easy to detect subsurface defects and subtle defects. According to the inspection results the stress concentrates in gear surface, some internal defects and microscopic flaws exist on the gear units are not found to penetrate the nondestructive inspection, but magnetic nondestructive inspection could have found many defect. Therefore, a reasonable method of nondestructive inspection for the large gear units is suitable to magnetic nondestructive inspection.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.89-93
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• 2002

This paper introduces a vision-based on-line fabric inspection methodology of woven textile fabrics. Current procedure for determination of fabric defects in the textile industry is performed by human in the off-line stage. The advantage of the on-line inspection system is not only defect detection and identification, but also 벼ality improvement by a feedback control loop to adjust set-points. The proposed inspection system consists of hardware and software components. The hardware components consist of CCD array cameras, a frame grabber and appropriate illumination. The software routines capitalize upon vertical and horizontal scanning algorithms characteristic of a particular deflect. The signal to noise ratio (SNR) calculation based on the results of the wavelet transform is performed to measure any deflects. The defect declaration is carried out employing SNR and scanning methods. Test results from different types of defect and different style of fabric demonstrate the effectiveness of the proposed inspection system.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.5
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• pp.8-14
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• 2008

For nondestructive inspection of electron beam (EB) welding part in automotive power transmission assembly, a pulse-echo ultrasonic testing apparatus in water immersion has been applied using the ultrasonic waves with a frequency of 10MHz. However various problems have appeared during the ultrasonic inspection, which led to some significant mistakes in automatic quality evaluation of the welding parts. Experimental study showed that the state of water couplant medium containing some amount of contaminants, rusts and anti-corrosion agents had considerable influences on the reduction of ultrasonic amplitudes during wave propagation. The amplitude reduction depending on the coupling medium state could bring about some mis-diagnoses for defects in the welding parts. The results proposed that for a reliable inspection of defects in welds the state of water medium should be kept in about 15 volume fractions (vol.%) of anti-corrosion agents and in minimized contaminants.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3416-3422
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• 2014

A shock absorber rod is located in the center of the absorber piston and is responsible for the reciprocating movement portion. If it has surface defects, the damping performance of product will be adversely affected. A rod surface has gloss by heat treatment. Therefore, it is difficult to find a defect, such as dust, imprints, and blowholes. Because a total inspection is achieved by visual inspection by workers, it causes eyestrain and the quality of the product is not constant. In this paper, a machine vision system was developed to find a defect using a line-scan camera. The machine can detect surface defects than 0.3mm. To minimize the occurrence probability of defects on the inspection process, the developed auto inspection system had an automatic feeding system and incorporated a protection system. Through the development of this system, which relies on the operator's visual inspection of the surface of the shock absorber, the Rod inspection system constructed quality inspection standards and standardized tests to ensure improved reliability.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.6 s.261
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• pp.651-658
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• 2007

A new tree-structured neural network classifier is proposed for the automatic real-time inspection of cold-rolled steel strip surface defects. The defects are classified into 3 groups such as area type, disk type, area & line type in the first stage of the tree-structured neural network. The defects are classified in more detail into 11 major defect types which are considered as serious defects in the second stage of neural network. The tree-structured neural network classifier consists of 4 different neural networks and optimum features are selected for each neural network classifier by using SFFS algorithm and correlation test. The developed classifier demonstrates very plausible result which is compatible with commercial products having high world-wide market shares.