• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2059-2064
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• 2004

Texture analysis is an important role for automatic visual insfection. This paper presents an application of wavelet extension and Gray level co-occurrence matrix (GLCM) for detection of defect encountered in textured images. Texture characteristic in low quality images is not to easy task to perform caused by noise, low frequency and small dimension. In order to solve this problem, we have developed a procedure called wavelet image extension. Wavelet extension procedure is used to determine the frequency bands carrying the most information about the texture by decomposing images into multiple frequency bands and to form an image approximation with higher resolution. Thus, wavelet extension procedure offers the ability to robust feature extraction in images. Then the features are extracted from the co-occurrence matrices computed from the sub-bands which performed by partitioning the texture image into sub-window. In the detection part, Mahalanobis distance classifier is used to decide whether the test image is defective or non defective.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.525-534
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• 2013

Recently, mura defect inspection techniques are receiving attention in LCD production procedure since demands of TFT-LCD are growing. In this paper, we propose an automatic mura defect inspection method using gabor wavelet transform and DCT. First, we generate a reference panel image using DCT based method. For original panel image and generated reference panel image, we apply a gabor wavelet transform to eliminate texture information in images. Then, we extract mura defect regions from the difference image between gabor wavelet transform image of original panel and generated reference panel image. Finally, all mura defect regions are quantified to detect accurate mura defects. Experimental results show that our method is more accurate and efficient than previous methods.

• Journal of Navigation and Port Research
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• v.28 no.1
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• pp.43-49
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• 2004

Defects inspection of commodities are very important with those design and manufacturing process and essential to strengthen the competitiveness of those. If on-line automatic defects detection is performed without damaging to products, the production cost shall be curtailed through the reducing man-power, economical management of Q.C(Quality Control). In this paper, it is suggested three spatial filtering methods which can extract the necessary information in case of defects being on the surface of object like iron plate. In addition, the dependence of filtering characteristics on parameters such as the pitch and width of slits is analyzed and the surface defect detection system is constructed. Several experiments were carried out for determining the adequate spatial filtering method through comparing and analyzing effects of parameters like defect's size and shape, intensity of light, noise of coherent source and slit number.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.10
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• pp.1508-1515
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• 2017

This paper proposes the defect detection method for automatic inspection machines in printed circuit boards (PCBs) manufacturing system. The defects of PCB such as open, short, pin hole and scratch can be detected by comparing the standard image and the target image. The standard image is obtained from CAD file such as ODB++ format, and the target image is obtained by arranging, filtering and binarization of captured PCB image. Since the PCB size is too large and image resolution is too high, the image processing requires a lot of memory and computational time. The wavelet transform is applied to compress the standard and target images, which results in reducing the memory and computational time. To increase the inspection accuracy, we utilize the he HH-domain as well as LL-domain of the transformed images. Experimental results are finally presented to show the performance improvement of the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1295-1297
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• 2008

Large-sized flat-panel displays are widely used for PC monitors and TV displays. In this paper, frequency domain pre-filter algorithms are presented for detection of defects in large-sized Thin Film Transistor-Liquid Crystal Display(TFT-LCD) panel surfaces. Frequency analysis with 1-D, 2-D FFT methods for extract the periodic patterns of lattice structures in TFT-LCD is performed. To remove this patterns, frequency domain band-stop filters were used for eliminating specific frequency components. In order to acquire only defected images, 2-D inverse FFT methods to inverse transform of frequency domain images were used.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.595-601
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• 2005

A mobile robot system utilizing NDT (Non-Destructive Testing) method is designed and fabricated f3r automatic integrity evaluation of large sized industrial reservoirs and pipelines. The developed mobile robot can crawl over the outer surface of the industrial facilities even though the shape of the structures is various and unsymmetric. The robot detects defects such as pinholes, cracks and thickness reduction at the wall of the facilities using EMAT (Electro-Magnetic Acoustic Transducer). Image processing technology for weld line detection at the surface of the target and host programs including defect detecting algorithms are also developed. Automation of defect detection for these kinds of large facilities using mobile robots is helpful to prevent significant troubles of the structures without danger of human beings under harmful environment.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.7
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• pp.619-625
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• 2015

There is a large interest to find reliable and automatic methods for crack detection and quantification in the railway bogie frame. The non-destructive inspection of railway bogie frame has been performed by ultrasonic and magnetic particle testing in general inspection. The magnetic particle method has been utilized in the defect inspection of the bogie frame but the grinding process is required before inspection and the dust is developed resulting from the processing. The objective of this paper is to apply the inspection method of bogie frame using infra-red thermography. The infra-red thermography system using the excitation of eddy current was performed for the defect evaluation of weld specimen inserted artificial defects. The result shows that the infra-red thermography method can detect the surface and inner defects in weld specimen for bogie frame.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1018-1020
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• 2013

Conventionally, PCB fabrication processes detects simply electrical characteristics of TCP and COF by automatic manufacturing system and additionally, by introducing human visual detection, those are very ineffective in view of low cost implementation. So, this paper presents an efficient detection algorithm for short and protrusion-type defects based on reference images by using local binary pattern analysis. The proposed methods include several preprocessing techniques such as histogram equalizing, the compensation of spatial position and maximum distortion coordination Through several experiments, it is shown that the proposed method can improve the defect detection performance compared to the conventional schemes.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.11-20
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• 2015

Typically welded bellows are checked with human eye and microscope, and then go through leakage test of gas. The proposed system alternates these heuristic techniques using support vector machines. Image procedures in the proposed method can cover the irregularity problem induced from human being. To get easy observation through microscope, 3D display system is also exploited. Experimental results from this automatic measurement show the welding detection is done within one tenth of permitted error range.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1991.11a
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• pp.87-94
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• 1991

This Paper is to aim the microdefect evaluation of semiconductor Package into a quantitative from NDI's image processing of ultrasonic wave. Accordingly, for the detection of delamination between the Joining condition of boundary microdefect of semiconductor packaga the result from sampling original image, histogramming, binary image or image processing of multinumerloal value is such as the follows. ([) The least limitation from the microdefect detection of the semiconductor package by surveying high ultrasonic wave seems to be about 0.8 $\mu\textrm{m}$ in degree. (2) A result of applying the image processing of multinumerical value to the semiconductor package it was possible to devide the Category into the effectiveness.