• 한국멀티미디어학회논문지
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• 제18권9호
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• pp.1039-1046
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• 2015

We propose a feature generation method for low-resolution face recognition. For this, we first generate new features from the input features (pixels) of a low-resolution face image by adding the higher-order terms. Then, we evaluate the separability of both of the original input features and new features by computing the discriminant distance of each feature. Finally, new data sample used for recognition consists of the features with high separability. The experimental results for the FERET, CMU-PIE and Yale B databases show that the proposed method gives good recognition performance for low-resolution face images compared with other method.

• 전기학회논문지
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• 제64권1호
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• pp.82-89
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• 2015

The researches of image recognition have been processed traditionally. Especially, face recognition technology has been received attractions with advance and applied to various areas according as camera sensor embedded into many devices such as smart phone. In this study, we design and develop a feature vector generation technique of face for making animation caricatures using methods for face detection which are previous stage of face recognition. At first, we detect both face region and detailed eye region of component element by Viola&Johns's realtime detection method which are called as ROI(Region Of Interest). And then, we generate feature vectors of eye region by utilizing factors as opposed to the periphery and by using appearance information of eye. At this point, we focus on the embedded information in many color spaces to overcome the problems which can be occurred by using one color space. We propose a feature vector generation method using information from many color spaces. Finally, we experiment the test of feature vector generation by the proposed method with enough quantity of sample picture data and evaluate the proposed method for factors of estimating performance such as error rate, accuracy and generation time.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2209-2212
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• 2003

In this paper, we propose the method to extract the important frequency bands from the EMG signal, and for generation of feature vector using the important frequency bands. The EMG signal is measured with 4 sensor and is recorded as 4 channel’s time series data. The same frequency bands from 4 channel’s frequency components are selected as the important frequency bands. The feature vector is calculated by the function formed using the combination of selected same important frequency bands. The EMG signals acquired from seven wrist motion type are recognized by changing into the feature vector formed. Then, the extraction and generation is performed by using the double combination of the genetic algorithm (GA) and the neural network (NN). Finally, in order to illustrate the effectiveness of the proposed method, computer simulations are done.

• 한국CDE학회논문집
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• 제8권2호
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• pp.122-132
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• 2003

STEP AP218 has a standard schema to represent the structural model of a midship section. While it helps to exchange ship structural models among heterogeneous automation systems, most shipyards and classification societies still exchange information using 2D paper drawings. We propose a feature parameter input method to generate a 3D STEP model of a ship structure from 2D drawings. We have analyzed the ship structure information contained in 2D drawings and have defined a data model to express the contents of the drawing. We also developed a QUI for the feature parameter input. To translate 2D information extracted from the drawing into a STEP AP2l8 model, we have developed a shape generation library, and generated the 3D ship model through this library. The generated 3D STEP model of a ship structure can be used to exchange information between design departments in a shipyard as well as between classification societies and shipyards.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2007년도 춘계 학술대회논문집
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• pp.103-107
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• 2007

Computational Fluid Dynamics (CFD in short) approach is now playing an important role in the engineering process recently. Generating proper grid system for the region of interest in time is prerequisite for the efficient numerical calculation of flow physics using CFD approach. Grid generation is, however, usually considered as a major obstacle for a routine and successful application of numerical approaches in the engineering process. CFD approach based on the unstructured grid system is gaining popularity due to its simplicity and efficiency for generating grid system compared to the structured grid approaches. In this paper an automated triangular surface grid generation using CAD surface data is proposed According to the present method, the CAD surface data imported in the STL format is processed to identify feature edges defining the topology and geometry of the surface shape first. When the feature edges are identified, node points along the edges are distributed. The initial fronts which connect those feature edge nodes are constructed and then they are advanced along the CAD surface data inward until the surface is fully covered by triangular surface grid cells using Advancing Front Method. It is found that this approach can be implemented in an automated way successfully saving man-hours and reducing human-errors in generating triangular surface grid system.

• 한국전산유체공학회지
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• 제12권4호
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• pp.68-73
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• 2007

Computational Fluid Dynamics (CFD) approach is now playing an important role in the engineering process in these days. Generating proper grid system in time for the region of interest is prerequisite for the efficient numerical calculation of flow physics using CFD approach. Grid generation is, however, usually considered as a major obstacle for a routine and successful application of numerical approaches in the engineering process. CFD approach based on the unstructured grid system is gaining popularity due to its simplicity and efficiency for generating grid system compared to the structured grid approaches, especially for complex geometries. In this paper an automated triangular surface grid generation using CAD(Computer Aided Design) surface data is proposed. According to the present method, the CAD surface data imported in the STL(Stereo-lithography) format is processed to identify feature edges defining the topology and geometry of the surface shape first. When the feature edges are identified, node points along the edges are distributed. The initial fronts which connect those feature edge nodes are constructed and then they are advanced along the CAD surface data inward until the surface is fully covered by triangular surface grid cells using Advancing Front Method. It is found that this approach can be implemented in an automated way successfully saving man-hours and reducing human-errors in generating triangular surface grid system.

• 정보보호학회논문지
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• 제31권6호
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• pp.1279-1290
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• 2021

차량 기술이 성장하면서 운전자의 개입이 필요 없는 자율주행까지 발전하였고, 이에 따라 차량 내부 네트워크인 CAN 보안도 중요해졌다. CAN은 해킹 공격에 취약점을 보이는데, 이러한 공격을 탐지하기 위해 기계학습 기반 IDS가 도입된다. 하지만 기계학습은 높은 정확도에도 불구하고 적대적 예제에 취약한 모습을 보여주었다. 본 논문에서는 IDS를 회피할 수 있도록 feature에 잡음을 추가하고 또한 실제 차량의 physical attack을 위한 feature 선택 및 패킷화를 진행하여 IDS를 회피하고 실제 차량에도 공격할 수 있도록 적대적 CAN frame 생성방법을 제안한다. 모든 feature 변조 실험부터 feature 선택 후 변조 실험, 패킷화 이후 전처리하여 IDS 회피실험을 진행하여 생성한 적대적 CAN frame이 IDS를 얼마나 회피하는지 확인한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.2919-2937
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• 2020

Post-Quantum Cryptography (PQC) is rapidly developing as a stable and reliable quantum-resistant form of cryptography, throughout the industry. Similarly to existing cryptography, however, it does not prevent a third-party from using the secret key when third party obtains the secret key by deception, unauthorized sharing, or unauthorized proxying. The most effective alternative to preventing such illegal use is the utilization of biometrics during the generation of the secret key. In this paper, we propose a biometric-based secret key generation scheme for multivariate quadratic signature schemes, such as Rainbow. This prevents the secret key from being used by an unauthorized third party through biometric recognition. It also generates a shorter secret key by applying Principal Component Analysis (PCA)-based Confidence Interval Analysis (CIA) as a feature extraction method. This scheme's optimized implementation performed well at high speeds.

• 융합신호처리학회논문지
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• 제14권4호
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• pp.217-221
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• 2013

최근, 이진 특징 기술자를 생성하는 방법에 대한 연구가 많이 진행되고 있다. 이진 특징 기술자의 정합은 비트 연산에 기반한 해밍거리를 이용하므로 실수 연산에 기반한 유클리디안 거리를 이용하는 기존의 일반적인 특징 기술자의 정합보다 훨씬 효율적이기 때문이다. 그러나, 특징 수의 증가는 정합 속도를 선형적으로 감소시키는 원인이 되기 때문에, 객체 추적과 같은 실시간 처리가 중요한 응용 분야에서는 이진 특징 기술자의 정합 속도를 더욱 향상시킬 수 있는 방법에 대한 요구가 증가해 왔다. 이에 본 논문에서는 고차원의 이진 특징 기술자를 여러 저차원의 이진 특징 기술자로 나누어 부분 해밍거리를 계산하고 순차적으로 분석함으로써, 정합 속도는 크게 개선하면서도 정확도는 유지할 수 있는 방법을 제안한다. 제안된 방법의 효율성을 분석하기 위해 기존의 정합 방법들과의 비교 실험을 수행한다. 아울러, 제안된 고속화 방법의 성능을 극대화하기 위한 이진 특징 기술자 생성 방법에 대해서도 논의한다. 몇가지 생성 방법에 대한 성능을 분석함으로써, 가장 효과적인 방법을 모색한다.

• 한국항만학회지
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• 제14권1호
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• pp.97-105
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• 2000

This paper presents an automatic mesh generation considering water depth, which is based on the depth interpolation. The key feature of this method is that the position of a mesh on any depth in the shallow water area can be generated. The Examples are carried out, and the results are shown to be good. This method is shown to be a useful and powerful tool for the flow calculation for the seabed topography.