• Journal of Korea Multimedia Society
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• v.23 no.5
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• pp.633-640
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• 2020

Defect region segmentation of TFT-LCD images is performed by combining defect pixels detected by a defect detection method into defect region, or by using morphological operations to segment defect region. Therefore, the result of segmentation of the defect region is highly dependent on the defect detection result. In this paper, we propose a method which segments defect regions sequentially according to the possibility of being included in defect regions in TFT-LCD images. The proposed method repeats the process of detecting a seed using the median value and the median absolute deviation of the image, and segments the defect region using the seeded region growing method. We confirmed the superiority of the proposed method to segment defect regions using pseudo-images and real TFT-LCD images.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.73-83
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• 2015

This paper proposes a TFT-LCD defect blob detection algorithm using the sequential defect detection method. First, for every pixel, a defect possibility is determined by the intensity difference and the defect candidates are detected according to the sequential defect detection method. For detected candidate pixels, the defect probability that indicates a potential included in the defect according to the each step. By applying the morphological operation, blobs are comprised of the detected candidates and the defect blobs are detected using the defect possibility of blobs. The validity of the proposed method was demonstrated a simulated image and also then it was tested a real TFT-LCD image. By the experimental results, the proposed method is very effective in TFT-LCD detect detection.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.112-114
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• 1991

This paper describes an application of neural network to diagnose defect of induction motor and investigates possibility to construct defect diagnosis system to be operated without special knowledge. For defect diagnosis, frequency spectrum of vibration is utilized. Learning method of applied neural network is back propagation.

• Journal of the Korea Institute of Building Construction
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• v.7 no.4
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• pp.125-132
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• 2007

The use of Self-Leveling material is increasing recently. This paper assesses the quality of surface layer of concrete floor when Self-Leveling material is defective. The paper shows how to predict the defect of SL material before construction begins. The relationship between the quality of surface layer of concrete floor and the defect of SL material was determined and the quality of surface layer of concrete floor was then estimated. The relations between the quality of surface layer and the defect of SL material were determine considering surface strength, moisture, and consistency of surface layer. Absorbing amount was used as the indicator of consistency and the absorbing amount of test material was measured. Then the relations between the test material and surface strength were determined. Generally concrete floor with greater consistency has greater surface strength, however in this study, we hound that high impact concrete floor could have lower surface strength as the consistency gets bigger. The relations between the level of defect occurred in SL material and the quality of surface layer were examined and we clarified that the surface layer with lower consistency gets higher possibility to occur exfoliation in early stage, one or two weeks after constructing SL material. When the consistency is sufficient, the occurring situation of defect depends upon the moisture of surface layer. Little amount of moisture gets higher possibility not to occur the defect. As the amount increases, fissure generates and early exfoliation may occur. In addition, the level of fissure is highly related with the surface strength.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.123-130
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• 2014

In TFT-LCD panel images, defects are typically detected by using a large difference in the brightness compared to the background. In this paper, we propose a sequential defect detection algorithm according to defect possibility caused by difference of brightness. By using this method, pixels with high defect probabilities are preferentially detected and defects with a large brightness difference are accurately detected. Also, limited defects with a small brightness difference is detected more reliably, eventually minimizing the degree of over-detection. We have experimentally confirmed that our proposed method showed an excellent detection result for detecting limited defects as well as defects with a large brightness difference.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.195-198
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• 2001

Backside defect of plate structure may grow due to fatigue or overload to cause critical failure during operation, so it is important to detect this kind of defect in line. For this purpose, nondestructive, non-contact and highly sensitive method is required. ESPI and Shearography are considered as useful method to satisfy these requirements. In this paper, the possibility of application of ESPI and Shearography to detect the backside defect of steel plate and to quantify the defect size was tested. For the experiment, some steel plates with defect on the backside were prepared. Experimental results for these plates showed that location and size of defect could be detected correctly by both of ESPI and Shearography.

• Journal of the Korean Ceramic Society
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• v.42 no.1
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• pp.1-6
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• 2005

In aqueous alumina tape casting, the effects of altering the composition of the suspensions, the binders and the casting thickness were studied. The rheological behavior of the suspensions and the defects of the dried tapes were examined and the relationships between them are discussed. The changes in the defect regions reported in the previous paper were related with the rheological properties with variations of the binder, the composition and the casting thickness. The shear thinning factor increased with the organic content and the solid content (the decrease of water content). The apparent viscosity increased with the shear thinning factor. The relation between the shear thinning factor and the log apparent viscosity was similar for all binder types. In the relation between the defect free region and the rheological properties, the defect free region became narrower with increasing casting thickness. The defect free region is independent of binder type. Therefore, the thicker tape is more difficult to produce in aqueous alumina tape casting. Knowledge of the rheological properties of the suspensions could help Predict the defect type and the possibility of defect free dried tapes.

• Transactions of Materials Processing
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• v.21 no.5
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• pp.291-297
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• 2012

In this paper, the effect of back tension in multi-pass drawing or wiredrawing on the central bursting defect is investigated using finite element predictions. A rigid-plastic finite element method was used together with the McClintock damage model. Central bursting defects under different back tension stress values ranging from 0% to 20% of the yield strength of the material were predicted and they were compared to understand the effect of the back tension stress values on the central bursting defect. It is found that the level of back tension has a strong influence on the cumulative damage. Thus, higher back tension raises the possibility of the central bursting defect occurring, even though it decreases the interfacial pressure between the die and the work piece.

• 전자공학회논문지 IE
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• v.48 no.4
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• pp.1-6
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• 2011

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. From some experiments results, the proposed algorithms show that defect detected and classified in the ratio of 92.3% and 94.5 respectively. Accordingly, in this paper, a possibility of practical implementation of the LCD defect inspection system is finally suggested.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.6
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• pp.43-51
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• 2014

TFT-LCD image includes a defect of various properties. TFT-LCD image have a recognizable defects in the human inspector. On the other hand, it is difficult to detect defects that difference between the background and defect is very low. In this paper, we proposed sequentially detect algorithm from pixels included in the defect region to limited defects. And blob analysis methods using the blob size and gray difference are applied to the defect candidate image. Finally, we detect an accurate defect blob to distinguish the noise. The experimental results show that the proposed method finds the various defects reliably.