• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.413-416
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• 2005

Developement of computer and digitalizing of medical implement are being caused digitalizing of medical image. Medical Images are being managed more by PACS. In this situation comes out many problem about ownership, the right of properity of the medical images and notice wheather the data are modified. Digital watermarking can solve this problem. The proposed schemes have a two weak point that Non-blind method need a original image and Blind method use gaussian watermarking. In this paper, we propose a blind watermarking using binary image in order to easily recognize result of watermark This proposed scheme using wavelet transform and Circular Input method that input in medium-band of frequency domain.

• Journal of Navigation and Port Research
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• v.37 no.4
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• pp.337-343
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• 2013

To ensure the safety for vessels anchored in stormy weather, duty officer and VTS operator have to frequently check whether their anchors are dragging. To judge dragging of the anchored vessel, it is important for VTS operator to recognize the turning circle and its center of the anchored vessel. The judgement for the anchored vessel dragging can be made by using Radar and AIS. If it is available, CCTV or eye-sighting can be used to know the center of turing circle. However, the VTS system collects individual ship's dynamic information from AIS and ARPA radar and monitors of the anchored vessels, it is difficult for VTS operator not only to get the detailed status information of the vessels, but also to know the center of turning circle. In this study, we propose an efficient algorithm to estimate the center of turning circle of anchored vessel by using the ship's heading and position data, which were from AIS. To verify the effectiveness of the proposed algorithm, the experimental study was made for the anchored vessel under real environments.

• 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 the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.165-171
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• 2004

Owing to small sizes and high density to the semiconductor It, it is difficult to discriminate the defects of ICs by human eyes. High precision inspection system with computer vision is essentially established for the manufacturing process due to the variety of defective parts. Especially it is difficult to implement the algorithm for the coplanarity of IC leads. Therefore in this paper, the inspection system which can detect the defects of the SOP types of ICs having 1cm${\times}$0.5cm of the chip size is implemented and evaluated it's performance. In order to optimally detect various items, some principles of geometry are theoretically presented , length measurement, pitch measurement, angle measurement, brightness of image and correcton of position. The interface circuit is designed for implementation of inspection system and connected the HANDLER. In the result, the system could detect two ICs' defects per second and confirmed the resolution of 20$\mu$m per pixel.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.163-166
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• 2006

The field of medical images has been digitalized as the development of computer and the digitalization of the medical instruments. As a result it causes a lot of problems such as an illegal copy related to medical images and property right of the medical images. Therefore, digital watermarking is used for discrimination whether the data are modified or not. It is also used to protect both the property right of medical images and the private life of many patients. The proposed theories, the Non-blind and the Blind method, have two problems. One is needed an original image and the other is using a gaussian watermarking. This paper proposes the new Blind Watermarking using binary images in order to easily recognize the results of watermark. This algorithm is described that an watermark of a binary image is wavelet-transformed, and then a transformed watermark is inserted in medium-band of frequency domains of original image by the Circular Input method. The propose method presented the good performance of over 0.97 in NC.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.4
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• pp.23-29
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• 2002

Radar method can be effective in probing concrete structures damaged by earthquake. Data analysis is usually performed in time domain, by considering time delay of the wave due to the dielectric constant of concrete. In this study, improved data analysis has been performed using signal processing scheme of spectra analysis and filtering. Three antenna with 900MHz, 1㎓, and 1.5㎓ center frequency were used to detect a steel bar or delamination in specimens for obtaining data, Frequency spectrum was filtered in low pass, high pass, and band pass varying cutoff frequency with 1/3 octave in frequency domain. The most effective cutoff frequency for each frequency has been determined as the range for 2 octave lower to 1 octave higher and 2 octave lower to 1 octave lower. This result provided a basis in improving data analysis capability using frequency domain filtering.

• Journal of the Korean GEO-environmental Society
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• v.14 no.4
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• pp.47-52
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• 2013

In Korea, the number of mining operations are getting smaller. But buried accidents are on the increase every year. For this reason, it is important to safety management in construction process, especially the worker's safety. In the field of construction needs utilization of integration system according to purpose of utilization, particularly in underground construction sites utilizing is emphasized even more. The current element technologies of location tracking, sensors and wireless communication possible to utilize but it is still difficult to utilization of integration system in construction field because a study is not complete on commercialization and availability. In this study, for real time 3-dimensional management of ubiquitous construction site in ground and underground, measure data using MEMS sensor, EDM and DGPS in 2 test site. Also results were analysed by MATLAB. As a result, error is verification less than 3 meter that possible to distinguish with the naked eye and construct direction of study based on result of former.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.555-563
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• 2018

Thermal infrared images have the characteristic of being able to detect objects that can not be seen with the naked eye and have the advantage of easily obtaining information of inaccessible areas. However, TIR (Thermal InfraRed) images have a relatively low spatial resolution. In this study, the applicability of the pansharpening algorithm used for satellite imagery on images acquired by the UAV (Unmanned Aerial Vehicle) was tested. RGB image have higher spatial resolution than TIR images. In this study, pansharpening algorithm was applied to TIR image to create the images which have similar spatial resolution as RGB images and have temperature information in it. Experimental results show that the pansharpening algorithm using the PC1 band and the average of RGB band shows better results for the quantitative evaluation than the other bands, and it has been confirmed that pansharpening results by ATWT (${\grave{A}}$ Trous Wavelet Transform) exhibit superior spectral resolution and spatial resolution than those by HPF (High-Pass Filter) and SFIM (Smoothing Filter-based Intensity Modulation) pansharpening algorithm.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.87-93
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• 2019

Microcapsules were prepared by using a mixture of linseed oil and a small amount of fluorescent fluid as a core material. Self-healing protective coatings were prepared by applying coating formulations containing varying amounts of microcapsules on mortar surface. After scratch or crack was generated in the coating, when the damaged region was exposed to ultraviolet light (${\lambda}=365nm$), it was observed that fluorescence emission area increased with increasing microcapsule loading. In the cases of the self-healing coatings having 20wt% or more microcapsule loading, the damaged region was almost filled with the healing agent. In water sorptivity test, the self-healing coating having 20wt% or more microcapsule loading showed a healing efficiency of about 85%. The fluorescence emission from the damaged region was easily observed at a distance of 3 m. The self-healing protective coating is expected to be useful to confirm its self-healing function with the eye.

• Smart Media Journal
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• v.11 no.11
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• pp.92-98
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• 2022

Identifying defects in textiles is a key procedure for quality control. This study attempted to create a model that detects defects by analyzing the images of the fabrics. The models used in the study were deep learning-based VGGNet and ResNet, and the defect detection performance of the two models was compared and evaluated. The accuracy of the VGGNet and the ResNet model was 0.859 and 0.893, respectively, which showed the higher accuracy of the ResNet. In addition, the region of attention of the model was derived by using the Grad-CAM algorithm, an eXplainable Artificial Intelligence (XAI) technique, to find out the location of the region that the deep learning model recognized as a defect in the fabric image. As a result, it was confirmed that the region recognized by the deep learning model as a defect in the fabric was actually defective even with the naked eyes. The results of this study are expected to reduce the time and cost incurred in the fabric production process by utilizing deep learning-based artificial intelligence in the defect detection of the textile industry.