• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.147-148
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• 2012

With the rise of BIM application and green building assessment, studies on assessment of CO₂ emissions from buildings using BIM are needed. In accordance with the requirements, this study aims at developing BIM Template database, as a part of development of CO₂ assessment technology using BIM. Based on the research of construction materials, this study develops database by applying Procurement Agency Item Code to BIM Template. The results of this research makes it possible to assess CO₂ emissions of materials with BIM Template and building data modeling implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2237-2253
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• 2017

For the existing security problem based on Fuzzy Vault algorithm, we propose a cancelable fingerprint template encryption scheme in this paper. The main idea is to firstly construct an irreversible transformation function, and then apply the function to transform the original template and template information is stored after conversion. Experimental results show it effectively prevents the attack from fingerprint template data and improves security of the system by using minutiae descriptor to encrypt abscissa of the vault. The experiment uses public FVC2004 fingerprint database to test, result shows that although the recognition rate of the proposed algorithm is slightly lower than the original program, but the improved algorithm security and complexity are better, and therefore the proposed algorithm is feasible in general.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.700-705
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• 2008

In this paper, we propose object classification algorithm for real-time surveillance system. We have approached this problem using silhouette-based template matching. The silhouette of the object is extracted, and then it is compared with representative template models. Template models are previously stored in the database. Our algorithm is similar to previous pixel-based template matching scheme like Hausdorff Distance, but we use 1D image array rather than 2D regions inspired by Hilbert Path. Transformation of images could reduce computational burden to compute similarity between the detected image and the template images. Experimental results show robustness and real-time performance in object classification, even in low resolution images.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.205-214
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• 2020

With the recent development of hardware and software technology, interest in the development of wearable devices is increasing. In particular, wearable devices require algorithms suitable for low-power and low-capacity embedded devices. Among them, there is an increasing demand for a signal compression algorithm that reduces communication overhead, in order to increase the efficiency of storage and transmission of electrocardiogram (ECG) signals requiring long-time measurement. Because normal beats occupy most of the signal with similar shapes, a high rate of signal compression is possible if normal beats are represented by a template. In this paper, we propose an algorithm for determining the normal beat template using the template cluster and Pearson similarity. Also, the template is expressed effectively as a few vertices through linear approximation algorithm. In experiment of Datum 234 of MIT-BIH arrhythmia database (MIT-BIH ADB) provided by Physionet, a compression ratio was 33.44:1, and an average distribution of root mean square error (RMSE) was 1.55%.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.4
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• pp.80-86
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• 2017

The purpose of this study is to construct a pattern database of pipes and cavities buried in the ground to prevent ground subsidence. To do this, it developed a pattern template algorithm using Open CV and applied it to the results of GPR detection results of tank. As a result, proper pattern database construction was possible. Since the results of this study are based only on limited experimental results, it is expected that more realistic data will be constructed if various field data and detection results of large test beds are supplemented in the future.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.885-886
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• 2008

This paper presents a reference template design method for frame-based classification of underwater transient signals. In the proposed method, framebased feature vectors of each reference signal are clustered by using LBG clustering algorithm to reduce the number of feature vectors in each class. Experimental results have shown that drastic reduction of the reference database can be achieved while maintaining the classification performance with LBG clustering algorithm.

• Journal of Korea Multimedia Society
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• v.16 no.10
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• pp.1156-1162
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• 2013

Face verification has been widely studied during the past two decades. One of the challenges is the rising concern about the security and privacy of the template database. In this paper, we propose a secure face verification system which generates a unique secure cryptographic key from a face template. The face images are processed to produce face templates or codes to be utilized for the encryption and decryption tasks. The result identity data is encrypted using Advanced Encryption Standard (AES). Distance metric naming hamming distance and Euclidean distance are used for template matching identification process, where template matching is a process used in pattern recognition. The proposed system is tested on the ORL, YALEs, and PKNU face databases, which contain 360, 135, and 54 training images respectively. We employ Principle Component Analysis (PCA) to determine the most discriminating features among face images. The experimental results showed that the proposed distance measure was one the promising best measures with respect to different characteristics of the biometric systems. Using the proposed method we needed to extract fewer images in order to achieve 100% cumulative recognition than using any other tested distance measure.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.05a
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• pp.302-303
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• 2004

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.5-12
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• 2004

The data transformation between XML and Relation Database is made through the Principle of mapping bewtween them. There are two ways to access SQL Server, one is to assign SQL query to URL and the other is to use template file. MS-SQL server takes advantage of OpenXML function to transform the results of executing SQL query into XML documents. That is, OpenXML first makes node tree and then transforms row set data of XML documents into XML data of relation type. In order to insert XML data into database data. data is extracted from parsing XML documents using sp_xml_preparedocument procedure, and then the document structure is mapped into tree structure and stored in a table of database. Consequently, Data transformation between XML and Relation Database is made through mapping bewtween them. This article proposes the principle of mapping between XML and Relation Database and then shows the implementation of transformation between them so that it introduces the possibilty of bringing the extension and efficiency of data and various effects.

• Journal of KIISE:Databases
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• v.34 no.2
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• pp.99-108
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• 2007

In this paper, we design and implement the Film Defect Inspection System (FDIS) that detects film defects and determines their types which can be used for producing polarized films of TFT-LCD. The proposed system is designed to detect film defects from polarized film images using image segmentation techniques and to determine defect types through the image analysis of detected defects. To determine defect types, we extract features such as shape and texture of defects, and compare those features with corresponding features of referential images stored in a template database. Experimental results using FDIS show that the proposed system detects all defects of test images effectively (Precision 1.0, Recall 1.0) and efficiently (within 0.64 second in average), and achieves the considerably high correctness in determining defect types (Precision 0.96 and Recall 0.95 in average). In addition, our system shows the high robustness for rotated transformation of images, achieving Precision 0.95 and Recall 0.89 in average.