• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.784-793
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• 2012

Defects of TFT-LCD is detected by thresholding the difference image between the input image and template one because LCD panel has its inherent patterns. However, the pitch corresponding to pattern period is gradually changed according to the distance from the center of camera due to geometric distortion of camera characteristics. This paper presents a method to detect defects through comparing the pitch area with neighbor pitch areas where the perspective transform is performed with the extracted features to correct the distortion. The experimental results show that the performance of the proposed method is very effective for real data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.7 s.166
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• pp.1065-1074
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• 1999

This study proposes the analysis and evaluation method of time series ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaotic time series signal analysis quantitatively welding defects. For this purpose analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaoticity resulting from distance shills such as 0.5 and 1.0 skip distance. Such differences in chaoticity enables the evaluation of unique features of defects in the weld zone. In experiment fractal(correlation) dimension and Lyapunov exponent extracted from 6dB ultrasonic defect signals of weld zone showed chaoticity. In quantitative chaotic feature extraction, feature values(mean values) of 4.2690 and 0.0907 in the case of porosity and 4.2432 and 0.0888 in the case of incomplete penetration were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaotic feature extraction in this study enhances ultrasonic pattern recognition results from defect signals of weld zone such as vertical hole.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.435-442
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• 2018

This study implemented an FPGA-based system to extract PCB defect patterns. The FPGA-based system can perform pattern matching at high speed for vision automation. An image processing library that is used to extract defect patterns was also implemented in IPs to optimize the system. The IPs implemented are Camera Link IP, Histogram IP, VGA IP, Horizontal Projection IP and Vertical Projection IP. In terms of hardware, the FPGA chip from the Vertex-5 of Xilinx was used to receive and handle images that are sent from a digital camera. This system uses MicroBlaze CPU. The image results are sent to PC and displayed on a 7inch TFT-LCD and monitor.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.2
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• pp.146-153
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• 2011

Model based machine condition diagnosis methods are generally using a normal and many failure models which need sufficient data to train the models. However, data, especially for failure modes of interest, is very hard to get in real applications. So their industrial applications are either severely limited or impossible when the failure models cannot be trained. In this paper, continuous hidden Markov model(CHMM) with only a normal model has been suggested as a very promising machine condition diagnosis method which can be easily used for industrial applications. Generally hidden Markov model also uses many pattern models to recognize specific patterns and the recognition results of CHMM show the likelihood trend of models. By observing this likelihood trend of a normal model, it is possible to detect failures. This method has been successively applied to arc weld defect diagnosis. The result shows CHMM's big potential as a machine condition monitoring method.

• Journal of the Korea Safety Management & Science
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• v.11 no.1
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• pp.27-33
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• 2009

A study of fracture to material is getting interest in nuclear and aerospace industry as a viewpoint of safety. Acoustic emission (AE) is a non-destructive testing and new technology to evaluate safety on structures. In previous research continuously, all tensile tests on the pre-defected coupons were performed using the universal testing machine, which machine crosshead was move at a constant speed of 5mm/min. This study is to evaluate an AE source characterization of SM45C steel by using k-nearest neighbor classifier, k-NNC. For this, we used K-means clustering as an unsupervised learning method for obtained multi -variate AE main data sets, and we applied k-NNC as a supervised learning pattern recognition algorithm for obtained multi-variate AE working data sets. As a result, the criteria of Wilk's $\lambda$, D&B(Rij) & Tou are discussed.

• 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.15 no.1
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• pp.185-192
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• 2010

This research suggests that valuate similarities by using the matches of patterns which is appeared on different two documents. Statistical ways such as fingerprint method are mainly used for evaluate similarities of existing documents. However, this method has a problem of accuracy for the high similarity which is occurred when many similar words are appeared from two irrelevant documents. These issues are caused by simple comparing of statistical parameters of two documents. But the method using patterns suggested on this research solved those problems because it judges similarity by searching same patterns. This method has a defect, however, that takes long time to search patterns, but this research introduce the algorithms complement this defect.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1507-1510
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• 2005

This study was carried out as a part of the research on the development of a maskless and electroless process for fabricating metal micro/nanostructures by using a nanoindenter and an electroless deposition technique. $2-\mu{m}-deep$ indentation tests on Ni and Cu samples were performed. The elastic recovery of the Ni and Cu was 9.30% and 9.53% of the maximum penetration depth, respectively. The hardness and the elastic modulus were 1.56 GPa and 120 GPa for Ni and 1.49 GPa and 100 GPa for Cu. The effect of single-point diamond machining conditions such as the Berkovich tip orientation (0, 45, and $90^{\circ}$) and the normal load (0.1, 0.3, 0.5, 1, 3, and 5 mN), on both the deformation behavior and the morphology of cutting traces (such as width and depth) was investigated by constant-load scratch tests. The tip orientation had a significant influence on the coefficient of friction, which varied from 0.52-0.66 for Ni and from 0.46-0.61 for Cu. The crisscross-pattern sample showed that the tip orientation strongly affects the surface quality of the machined area during scratching. A selective deposition of Cu at the pit-like defect on a p-type Si(111) surface was also investigated. Preferential deposition of the Cu occurred at the surface defect sites of silicon wafers, indicating that those defect sites act as active sites for the deposition reaction. The shape of the Cu-deposited area was almost the same as that of the residual stress field.

• Journal of Advanced Marine Engineering and Technology
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• v.41 no.3
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• pp.251-257
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• 2017

In this paper, an algorithm for detecting defects in thin-film-transistor liquid-crystal display (TFT-LCD) cell images is presented. TFT-LCD cell images typically contain periodic cell patterns that make it difficult to detect defects. We propose an efficient and powerful algorithm for eliminating the cell patterns using magnitude spectrum analysis. The first step was to obtain a spectrum for a cell image using the Fourier transform while eliminating larger coefficients using an adaptive filter. Next, an image without the cell pattern was obtained by using the inverse Fourier transform. Finally, the defect pixels were detected using the STD algorithm. The validity of the proposed method was investigated using real TFT-LCD cell images. The experimental results indicate that the proposed technique is extremely effective for detecting defects in TFT-LCD cell images.

• Annals of Clinical Neurophysiology
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• v.2 no.1
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• pp.13-20
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• 2000

Background and Objective : Visual evoked potentials(VEPs) is considered to be a reliable diagnostic procedure for examining patients with anterior visual pathways. Some abnormalities in the recordings on monocular stimulation have been said to indicate retrochiasmal lesion, but less consistent results have been reported. This study is to evaluate the positive predictability of VEP for the detection of retrochiasmal lesion. Methods : We reviewed VEPs that could be interpreted as indicative of a retrochiasmal lesions, based on amplitude or latency asymmetry recorded on the left(O1) and right(O2) occipital regions. Bilateral absent VEPs on both recording(O1 and O2) without evidence of prechiasmal lesion were included. During 5 years, we identified 31 patients who met the above criteria and who had undergone magnetic resonance imaging(MRI) of brain(one patient underwent computerized tomography). Twenty three patients underwent pattern reversal VEPs and others underwent flash goggle VEPs. Results : Brain imagings were abnormal in 29 and were normal in 2. Of the 29 abnormal scans, lesions in posterior visual pathway were detected in 21 scans(predictive value=68%). The predictive value was not significantly different between flash goggle VEP(75%) and pattern reversal VEP(68%). The predictive value was higher in patient with visual field defect(100%) than those without visual field defect(25%). The pathologic nature of lesion also showed close relations to the predictive value. VEPs is usually paradoxically lateralized(78%), but not in all patients. Conclusion : VEPs abnormalities suggesting retrochiasmal lesion were usually corresponded with brain MRI findings. Diagnostic reliability could be increased when considering the visual field defect and nature of lesion. Therefore, the authors suggest that VEPs studies could be useful in evaluating the patients with the retrochismal lesion.