• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.51-56
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• 2007

Feature functions were used for the classification of music. The spectral roll-off, variance, average peak level, and class were chosen to make up a feature function vector. Among these, it is the spectral roll-off function that has a low-frequency to high-frequency ratio. To find the optimal roll-off point, the roll-off points from 0.05 to 0.95 were swept. The classification success rate was monitored as the roll-off point was being changed. The data that were used for the experiments were taken from the sounds made by a modern violin and a baroque one. Their shapes and sounds are similar, but they differ slightly in sound texture. As such, the data obtained from the sounds of these two kinds of violin can be useful in finding an adequate roll-off point. The optimal roll-off point, as determined through the experiment, was 0.85. At this point, the classification success rate was 85%, which was the highest.

• ETRI Journal
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• v.34 no.5
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• pp.791-794
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• 2012

We propose an efficient framework to realistically render 3D faces with a reduced set of points. First, a robust active appearance model is presented to detect facial features in the projected faces under different illumination conditions. Then, an adaptive simplification of 3D faces is proposed to reduce the number of points, yet preserve the detected facial features. Finally, the point model is rendered directly, without such additional processing as parameterization of skin texture. This fully automatic framework is very effective in rendering massive facial data on mobile devices.

• Journal of Multimedia Information System
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• v.3 no.2
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• pp.13-20
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• 2016

Biometric authentication for account-based mobile payment continues to gain attention because of improvements on sensors that can collect biometric information. We propose an enhanced method for mobile payment security based on biometric authentication. In this mobile payment system, the communication between the user and the relying party is based on public key infrastructure. This method secures both the key and the biometric template in the user side using fuzzy vault biometric cryptosystems, which is based on non-random chaff point generator. In this paper, we consider an important process for the common fuzzy vault system, that is, the feature extraction method. We evaluate various feature extraction methods to enhance the accurate performance of the system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.102-112
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• 2007

This paper includes an analysis of face recognition algorithm to design hardware and presents fixed point model in accordance with it. Face recognition algorithm detects the positions of face and eyes to make use of their feature data to detect and verify human faces. It distinguishes a particular user by means of comparing them with registered face features. To implement the face recognition algorithm into hardware, we developed its fixed point model by analyzing face feature parameters, face acquisition data, and feature detection parameters and operation structure.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.529-536
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• 2007

Registration between image and object space is a fundamental step in photogrammetry and computer vision. Along with rapid development of sensors - multi/hyper spectral sensor, laser scanning sensor, radar sensor etc., the needs for registration between different sensors are ever increasing. There are two important considerations on different sensor registration. They are sensor invariant feature extraction and correspondence between them. Since point to point correspondence does not exist in image and laser scanning data, it is necessary to have higher entities for extraction and correspondence. This leads to modify first, existing mathematical and geometrical model which was suitable for point measurement to line measurements, second, matching scheme. In this research, linear feature is selected for sensor invariant features and matching entity. Linear features are incorporated into mathematical equation in the form of extended collinearity equation for registration problem known as photo resection which calculates exterior orientation parameters. The other emphasis is on the scheme of finding matched entities in the aide of RANSAC (RANdom SAmple Consensus) in the absence of correspondences. To relieve computational load which is a common problem in sampling theorem, deterministic sampling technique and selecting 4 line features from 4 sectors are applied.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.141-149
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• 2023

Repacked mobile apps constitute about 78% of all malware of Android, and it greatly affects the technical ecosystem of Android. Although many methods exist for repacked app detection, most of them suffer from performance issues. In this manuscript, a novel method using the Constant Key Point Selection and Limited Binary Pattern (CKPS: LBP) Feature extraction-based Hashing is proposed for the identification of repacked android applications through the visual similarity, which is a notable feature of repacked applications. The results from the experiment prove that the proposed method can effectively detect the apps that are similar visually even that are even under the double fold content manipulations. From the experimental analysis, it proved that the proposed CKPS: LBP method has a better efficiency of detecting 1354 similar applications from a repository of 95124 applications and also the computational time was 0.91 seconds within which a user could get the decision of whether the app repacked. The overall efficiency of the proposed algorithm is 41% greater than the average of other methods, and the time complexity is found to have been reduced by 31%. The collision probability of the Hashes was 41% better than the average value of the other state of the art methods.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.377-380
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• 2022

본 논문에서는 모바일 기반 AR 환경에서 RGB카메라로부터 얻은 영상 분석과 DB 기반의 특징점(Feature point) 매칭을 통하여 보다 정확하게 위험 상황을 알려줄 수 있는 프레임워크를 제안한다. 본 논문에서는 RANSAC(Random sample consensus)기반의 다중 평면 방식을 이용한 특징점을 추출하고 분석하여 영상에 존재하는 장애물을 감지한다. RGB카메라로 얻은 영상을 기반으로 장애물을 검출하는 접근법은 영상에 의존하기 때문에 조명에 따른 특징점 검출이 부정확하고, 조명이나 자연광 또는 날씨에 영향을 많이 받기 때문에 어둡거나 흐린 날씨에서는 장애물 검출이 어려워진다. 이 문제를 완화하기 위해 본 논문에서는 DB기반의 특징점 매칭을 통해 조명에 관계없이 장애물을 효율적이고 정확하게 감지한다. 특징점 매칭을 이용하려면 우선 영상에서 특징점이 안정적으로 추출될 수 있는 환경인, 조명이나 자연광이 충분한 환경에서 감지된 장애물 정보를 데이터베이스화 하여 저장한다. 조명이 충분하지 않은 환경에서 사용자가 사전에 저장된 지역에 근접할 경우 특징점 분석이 아닌 DB 기반 특징점 매칭을 통해 위험 요소를 감지한다. 우리의 방법은 조명의 여부의 관계없이 효과적으로 위험을 감지할 수 있기 때문에 다양한 분야에 활용될 수 있다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.9
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• pp.84-93
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• 1993

Recently, several nonlinear shape normalization methods have been proposed in order to compensate for the shape distortions in handwritten characters. In this paper, we review these nonlinear shape normalization methods from the two points of view : feature projection and feature density equalization. The former makes feature projection histogram by projecting a certain feature at each point of input image into horizontal-or vertical-axis and the latter equalizes the feature densities of input image by re-sampling the feature projection histogram. A systematic comparison of these methods has been made based on the following criteria: recognition rate, processing speed, computational complexity and measure of variation. Then, we present the result of quantitative evaluation of each method based on these criteria for a large variety of handwritten Hangul syllables.

• Proceedings of the Korean Society for Quality Management Conference
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• 2010.04a
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• pp.356-363
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• 2010

In this Paper, We study on establish for unit of measure. Quality means abstract for customer needs. we surveyed unit of measurement of quality feature of Juran, Taguchi, 6 sigma method. We suggest unit of measurement of quality feature. Each enterprise can use defining own unit of measurement of quality feature. Effect is expected in enterprise that these proposals do quality control. There is meaning in direction that measuring mean of quality feature that propose in this treatise understands actuality to be deeply and reconcile exact point of theory.

• Proceedings of the Safety Management and Science Conference
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• 2013.04a
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• pp.163-172
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• 2013

In this Paper, We study on establish for unit of measure. Quality means abstract for customer needs. we surveyed unit of measurement of quality feature of Juran, Taguchi, 6 sigma method. We suggest unit of measurement of quality feature. Each enterprise can use defining own unit of measurement of quality feature. Effect is expected in enterprise that these proposals do quality control. There is meaning in direction that measuring mean of quality feature that propose in this treatise understands actuality to be deeply and reconcile exact point of theory.