• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.325-333
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• 2010

Image registration involves overlapping images of an identical region and assigning the data into one coordinate system. Image registration has proved important in remote sensing, enabling registered satellite imagery to be used in various applications such as image fusion, change detection and the generation of digital maps. The image descriptor, which extracts matching points from each image, is necessary for automatic registration of remotely sensed data. Using contrast enhancement algorithms such as histogram equalization and image stretching, the normalized data are applied to the image descriptor. Drawing on the different spectral characteristics of high resolution satellite imagery based on sensor type and acquisition date, the applied normalization method can be used to change the results of matching interest point descriptors. In this paper, the matching points by scale invariant feature transformation (SIFT) are extracted using various contrast enhancement algorithms and injection of Gaussian noise. The results of the extracted matching points are compared with the number of correct matching points and matching rates for each point.

• Tribology and Lubricants
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• v.37 no.5
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• pp.164-171
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• 2021

Ultrasonic sensors show various reception characteristics based on the density of the measurement medium; hence, they are used in various fields to benefit from the characteristics of ultrasonic signals. In this study, the reception characteristics according to the thickness of the first matching layer are compared and analyzed for application to gas tank microleak detection. Accordingly, three types of sensors are manufactured with varying thicknesses of the first matching layer, namely 4.8 mm, 5.1 mm, and 5.5 mm; further, a direct measurement method is used wherein the sensor is attached to the inside of the chamber. Experiments are conducted to observe the phase change due to microleakage, which is the most linear in the sensor with the 4.8 mm thick first matching layer. This is assumed to be the result of stable signal transmission and reception with little phase deviations over time because the first matching layer is closest to the ultrasonic wavelength. The other sensors show nonlinear results with increasing thickness of the first matching layer. Through this study, it is found that appropriately selecting the thickness of the first matching layer of the ultrasonic sensor can greatly influence sensor reliability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1597-1610
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• 2022

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.834-835
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• 2016

In recent years, advances in technology, IT is rapidly growing. Accordingly, real time image processing and multiple platforms, providing compatibility with OpenCV for image processing technology research on actively in progress. At present, different, comparing the images to determine the similarity is low, the system will match the rate of people using the analogue figures to determine the system is for the most part. In this paper, Template Matching of OpenCV and Feature Matching utilizing different images to determine the similarity between digital values for the system. A comparison of the features of a specific point on the screen the image to extract the same feature in a different size, you can compare the features of the target image recognized as compared to three historic castle in comparison, verification. This is the voice and image recognition and analysis, check the matching rate readings than in Zhengzhou treatment techniques are available. The future of forensic and other image processing technologies for OpenCV studies will be needed to feed.

• The Journal of Advanced Prosthodontics
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• v.10 no.6
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• pp.422-429
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• 2018

PURPOSE. Accurate color matching of maxillofacial prostheses to skin is important for esthetics. A computerized color matching system specific to human skin has recently been developed. The purpose of this study was to evaluate the accuracy in color and translucency matching of the computerized color matching system across different skin colors. MATERIALS AND METHODS. The silicone was colored to simulate 28 different skin colors (n=5) to serve as "target skin colors". Using a spectrocolorometer (e-skin), color codes were determined for "replicate skin color" fabrication. CIELAB Delta-E between target skin color-replicate skin color pairs and translucency parameter were calculated. CIELAB Delta-E values were compared with one-way ANOVA and Tukey multiple-comparison. The agreement between $L^*$, $a^*$, $b^*$ and translucency parameter of target skin colors and replicate skin color were calculated by a two-way mixed average measures intraclass correlation coefficient. Translucency parameter of target skin color- replicate skin color pairs were compared with Paired t-test (${\alpha}=.05$). RESULTS. The mean CIELAB Delta-E value was 3.83 and significant differences were found among colors. The intraclass correlation coefficient showed excellent reliability for $L^*$, $a^*$, $b^*$ and good reliability for translucency parameter (P<.001). The mean translucency parameter of replicate skin colors was significantly higher than that of translucency parameter. CONCLUSION. The computerized color matching system specific to human skin was found to be reliable in terms of color and translucency between target skin colors and replicate skin color.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.319-323
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• 2005

As the software industry develops at a rate speed, anyone can copy or plagiarize without difficulty contents that are becoming digitalized. To make it worse, the development of various contents that be illegally copied and plagiarized are resulting in the increasing infringement on and the plagiarism of the intellectual property. This dissertation tries to put forth the method and the theory to effectively detect any plagiarism of the source code of programs realized in various languages. This dissertation analyzes the advantage and disadvantage of the plagiarism test software, and especially, presents a method to detect possible plagiarism by using the Pattern Matching to overcome its disadvantage. And it also intends to introduce more developed automatic detection system by overcoming the problems with the method of Pattern Matching.

• Proceedings of KOSOMES biannual meeting
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• 2005.11a
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• pp.191-196
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• 2005

The character strings on chips and components are so tiny and numerous that it is a very difficult work for people to perform. In paper, this we propose a mark automatic checking system, which will determine whether chip is wrong-mark or not by recognizing characters on chips. Lots of faulty detection conditions and template matching methods are used to inspect the faulty mark items. The faulty detection classifies conditions as five kinds-darkness, matching, area, broken and branch. A series of experimentation shan that the method proposed here am offer an effective way to determine wrong-mark on chips.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.670-674
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• 2005

$D^*$ criterion is defined as a reference of the handling quality and ride comfortableness for lateral-directional automobile motion. However it is generally difficult to obtain the satisfied handling quality and ride comfortableness based on $D^*$ criterion by conventional two wheel steering system. In this study, a design method of model matching control system is proposed to obtain the satisfied $D^*$ response of 4 Wheel Steering.

• Nuclear Engineering and Technology
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• v.36 no.3
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• pp.219-228
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• 2004

[1] and [2] present an approach to diagnosing possible defects in the mechanical systems of a nuclear power plant. In this paper, by using a fault library as a database and training data, we develop a diagnostic algorithm 1) to decide whether an Air Operated Valve system is sound or not and 2) to identify the defect from which an Air-Operated Valve system suffers, if any. This algorithm is composed of three stages: a neural net stage, a non-neural net stage, and an integration stage. The neural net stage is a simple perceptron, a pattern-recognition module, using a neural net. The non-neural net stage is a simple pattern-matching algorithm, which translates the degree of matching into a corresponding number. The integration stage collects each output and makes a decision. We present a simulation result and confirm that the developed algorithm works accurately, if the input matches one in the database.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1620-1627
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• 2017

In this paper, we design an observer-based $H_{\infty}$ fuzzy controller for interval type-2 Takagi-Sugeno (T-S) fuzzy systems under imperfect premise matching. The designed observer-based controller can effectively estimate the state of the system and make fuzzy system satisfy the $H_{\infty}$ disturbance attenuation performance. Using the slack matrix, the derived stabilization condition is expressed in terms of a linear matrix inequality. Finally, the effectiveness of the proposed method is verified through a simulation example.