• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.633-641
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• 2016

Automatic defect inspection system is composed of the step in the pre-processing, defect candidate detection, and classification. Polarizing films containing various defects should be minimized over-detection for classifying defect blobs. In this paper, we propose a defect detection algorithm using a skewness of histogram for minimizing over-detection. In order to detect up defects with similar to background pixel, we are used the characteristics of the local region. And the real defect pixels are distinguished from the noise using the probability density function. Experimental results demonstrated the minimized over-detection by utilizing the artificial images and real polarizing film images.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.55-61
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• 2021

In this paper, we proposed and implemented defect detection methods of polarized film with half-wave phase retardation plates. We investigated the principles of phase retardation compensation and optical principle of half-wave phase retardation plates. We analyzed of samples of polarized film with half-wave phase retardation plates. The optical defect detection methods are proposed and the performance is validated with experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1899-1907
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• 2013

This paper presents an efficient defect detection and classification system based on reference image for COF (Chip-on-Film) which encounters fatal defects after ultra fine pattern fabrication. These defects include typical ones such as open, mouse bite (near open), hard short and soft short. In order to detect these defects, conventionally it needs visual examination or electric circuits. However, these methods requires huge amount of time and money. In this paper, based on reference image, the proposed system detects fatal defect and efficiently classifies it to one of 4 types. The proposed system includes the preprocessing of the test image, the extraction of ROI, the analysis of local binary pattern and classification. Through simulations with lots of sample images, it is shown that the proposed system is very efficient in reducing huge amount of time and money for detecting the defects of ultra fine pattern COF.

• Journal of KIISE:Software and Applications
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• v.34 no.5
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• pp.447-454
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• 2007

TFT-LCD(Thin Film transistor liquid crystal display) has become actively used front panel display technology with increasing market. Intrinsically there is region of non uniformity with low contrast that to human eye is perceived as defect. As the gray level difference between the defect and the background is hardly distinguishable, conventional thresholding and edge detection techniques cannot be applied to detect the defect. Between the patterned and un-patterned LCD defects, this paper deals with un-patterned LCD defects by using independent component analysis, adaptive thresholding and skewness. Our method showed strong results even on noised LCD images and worked successfully on the manufacturing line.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.743-748
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• 2009

In this paper, we propose an effective method to extract background components in automated vision inspection system for polarized film used in TFT LCD display panels. The test image signals are typically composed of three components such as ununiform background, random noises and target defect signals. It is important to analyze the background signal for accurate extraction of defect components. Two dimensional continuous wavelets with first derivative gaussian is used. This methods can be applied for reliable extraction of defect signal by elimination of the background signal from the original image. The proposed method outperforms over conventional FFT methods.

• Journal of IKEEE
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• v.18 no.2
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• pp.234-239
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• 2014

This paper proposes a new automatic detection method to inspect mura defects on display film surface using morphological image processing and labeling. This automatic detection method for mura defects on display films comprises 3 phases of preprocessing with morphological image processing, Gabor filtering, and labeling. Since distorted results could be obtained with the presence of non-uniform illumination, preprocessing step reduces illumination components using morphological image processing. In Gabor filtering, mura images are created with binary coded mura components using Gabor filters. Subsequently, labeling is a final phase of finding the mura defect area using the difference between large mura defects and values in the periphery. To evaluate the accuracy of the proposed detection method, detection rate was assessed by applying the method in 200 display film samples. As a result, the detection rate was high at about 95.5%. Moreover, the study was able to acquire reliable results using the Semu index for luminance mura in image quality inspection.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.333-336
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• 2006

High Pressure Annealing System was developed to improve the characteristics of low-temperature poly-silicon thin film transistors.. (TFTs). The high-pressure steam annealing was applied to the poly-silicon film made by rapid thermal annealing method. The carrier lifetime was investigated by Microwave detection of the Photo-Conductive Decay and the increase of carrier lifetime which indicates the reduction of the defect was observed by high-pressure steam annealing of 1MPa 600C 1hour.

• Journal of the Semiconductor & Display Technology
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• v.11 no.2
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• pp.45-51
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• 2012

Multilayer co-extrusion blown film construction is a popular technique for producing plastic films for various packaging industries. Automated detection of defective films can improve the quality of film production process. In this paper, we propose a film inspection system that can detect and classify film defects robustly. In our system, first, film images are acquired through a high speed line-scan camera under an appropriate lighting system. In order to detect and classify film defects, an inspection algorithm is developed. The algorithm divides the typical film defects into two groups: intensity-based and texture-based. Intensity-based defects are classified based on geometric features. Whereas, to classify texture-based defects, a texture analysis technique based on local binary pattern (LBP) is adopted. Experimental results revealed that our film inspection system is effective in detecting and classifying defects for the multilayer co-extrusion blown film construction line.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.74-84
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• 2022

As the semiconductor industry develops, the difficulty of newly required process technology becomes difficult, and the importance of production yield and product reliability increases. As an effort to minimize yield loss in the manufacturing process, interests in the process defect process for facility diagnosis and defect identification are continuously increasing. This research observed the plasma condition changes in the multi oxide/nitride layer deposition (MOLD) process, which is one of the 3D-NAND manufacturing processes through optical emission spectroscopy (OES) and monitored the result of whether the change in plasma characteristics generated in repeated deposition of oxide film and nitride film could directly affect the film. Based on these results, it was confirmed that if a change over a certain period occurs, a change in the plasma characteristics was detected. The change may affect the quality of oxide film, such as the film thickness as well as the interfacial surface roughness when the oxide and nitride thin film deposited by plasma enhenced chemical vapor deposition (PECVD) method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.123-127
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• 1997

Recently, it is gradually raised necessity that interface is measured accurately and managed in industrial circles and medical world, An Ultrasonic wave transmitted from a focused beam transducer is being expected as a powerful tool for NDE of micro-defect. The ultrasonic NDE of the defect is based on the form of the wave reflected form the interface In this study, regarding to the thickness of film which is in opaque object and thickness measurement was done by MEM-cepstrum analysis of received ultrasonic wave. In measument results, film thickness which is beyond distance resolution capacity was measured accurately. Also, automatically repeated discrimination analysis method can be decided in the category of all kinds of defects on semiconductor package.