• Journal of Electrical Engineering and Technology
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• 제10권2호
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• pp.670-675
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• 2015

Medical imaging is one of the most powerful tools for gaining information about internal organs and tissues. It is a challenging task to develop sophisticated image analysis methods in order to improve the accuracy of diagnosis. The objective of this paper is to develop a Computer Aided Diagnostics (CAD) scheme for Brain Tumour detection from Magnetic Resonance Image (MRI) using active contour models and to investigate with several approaches for improving CAD performances. The problem in clinical medicine is the automatic detection of brain Tumours with maximum accuracy and in less time. This work involves the following steps: i) Segmentation performed by Fuzzy Clustering with Level Set Method (FCMLSM) and performance is compared with snake models based on Balloon force and Gradient Vector Force (GVF), Distance Regularized Level Set Method (DRLSE). ii) Feature extraction done by Shape and Texture based features. iii) Brain Tumour detection performed by various tree classifiers. Based on investigation FCMLSM is well suited segmentation method and Random Forest is the most optimum classifier for this problem. This method gives accuracy of 97% and with minimum classification error. The time taken to detect Tumour is approximately 2 mins for an examination (30 slices).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2405-2407
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• 2001

In this paper, we apply and evolutionary computation(EC), probabilistic optimization algorithm, to active contour. A number of problems exist associated with such as algorithm initialization, existence of local minima, non-convex search space, and the selection of model parameters in conventional models. We propose an adequate fitness function for these problems. The determination of fitness function adequate to active contour using EC is important in search capability. As a result of applying the proposed method to non-convex object shape, we improve the unstability and contraction phenomena, in nature, of snake generated in deformable contour optimization.

• Smart Structures and Systems
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• 제8권4호
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• pp.367-384
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• 2011

This paper presents the design and experimental evaluation of fast output sampling feedback controller to minimize structural vibration of a cantilever beam using Shape Memory Alloy (SMA) wires as control actuators and piezoceramics as sensor and disturbance actuator. Linear dynamic models of the smart cantilever beam are obtained using online recursive least square parameter estimation. A digital control system that consists of $Simulink^{TM}$ modeling software and dSPACE DS1104 controller board is used for identification and control. The effectiveness of the controller is shown through simulation and experimentation by exciting the structure at resonance.

• 로봇학회논문지
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• 제8권4호
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• pp.266-272
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• 2013

Facial feature extraction and tracking are essential steps in human-robot-interaction (HRI) field such as face recognition, gaze estimation, and emotion recognition. Active shape model (ASM) is one of the successful generative models that extract the facial features. However, applying only ASM is not adequate for modeling a face in actual applications, because positions of facial features are unstably extracted due to limitation of the number of iterations in the ASM fitting algorithm. The unaccurate positions of facial features decrease the performance of the emotion recognition. In this paper, we propose real-time facial feature extraction and tracking framework using ASM and LK optical flow for emotion recognition. LK optical flow is desirable to estimate time-varying geometric parameters in sequential face images. In addition, we introduce a straightforward method to avoid tracking failure caused by partial occlusions that can be a serious problem for tracking based algorithm. Emotion recognition experiments with k-NN and SVM classifier shows over 95% classification accuracy for three emotions: "joy", "anger", and "disgust".

• 융합신호처리학회논문지
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• 제4권2호
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• pp.1-6
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• 2003

본 연구는 스네이크를 이용하여 뇌의 자기 공명 영상에서 자동 혹은 반자동으로 종양 또는 병변의 정확한 윤곽선을 찾기 위함이다. 본 연구에서 기존의 스네이크가 가지고 있는 에너지 최적화 문제를 동적 프로그래밍을 이용하여 개선하였고, Image Force로 Canny Edge Detector의 값을 이용하여 스네이크가 잡음에 덜 민감하도록 하였다. 병변의 윤곽선이 추출되면, 병변의 면적, 중심 좌표, 둘레 등을 계산하도록 하였다 또한 병변에 대한 다수의 2차원 단면 영상을 합성하여 3차원으로 재구성하여 병변의 입체적인 모양을 볼 수 있도록 하였다. 본 연구에서 제안된 방법은 뇌종양 환자의 치료 계획 수립 뿐 아니라 경과를 평가하는데 유용하게 활용될 것으로 기대된다.

• 한국CDE학회논문집
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• 제13권6호
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• pp.403-411
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• 2008

The alignment of facial images is crucial for 2D face recognition. This is the same to facial meshes for 3D face recognition. Most of the 3D face recognition methods refer to 3D alignment but do not describe their approaches in details. In this paper, we focus on describing an automatic 3D alignment in viewpoint of quantitative analysis. This paper presents a framework of 3D face alignment and normalization based on feature points obtained by Active Shape Models (ASMs). The positions of eyes and mouth can give possibility of aligning the 3D face exactly in three-dimension space. The rotational transform on each axis is defined with respect to the reference position. In aligning process, the rotational transform converts an input 3D faces with large pose variations to the reference frontal view. The part of face is flopped from the aligned face using the sphere region centered at the nose tip of 3D face. The cropped face is shifted and brought into the frame with specified size for normalizing. Subsequently, the interpolation is carried to the face for sampling at equal interval and filling holes. The color interpolation is also carried at the same interval. The outputs are normalized 2D and 3D face which can be used for face recognition. Finally, we carry two sets of experiments to measure aligning errors and evaluate the performance of suggested process.

• 대한전자공학회논문지SP
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• 제44권6호
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• pp.84-92
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• 2007

본 연구는 원거리에서 걸음걸이 (보행)의 특성을 분석하여 인간을 식별하는 보행인식 (gait recognition) 기술을 다중 특징점 기반으로 확장하여 인식률 및 오류 내성을 향상시키는 기술을 제안한다. 보다 구체적으로 i)움직임 검출, ii) 객체 영역 검출, iii) 머리 영역 검출, 그리고, iv) 능동 형태 모델을 이용하여 기본 알고리듬 (gait baseline algorithm)의 문제점인 전처리 과정없이 그림자 영향과 낮은 인식률을 개선하였다. 제안된 알고리듬은 HumanID Gait Challenge (HGCD) 데이터집합을 이용한 실험을 통해 환경 변화요인에도 강건한 인간 보행인식이 가능함을 확인할 수 있다.

• Journal of Information Processing Systems
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• 제12권1호
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• pp.149-168
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• 2016

The Active Appearance Model (AAM) is a class of deformable models, which, in the segmentation process, integrates the priori knowledge on the shape and the texture and deformation of the structures studied. This model in its sequential form is computationally intensive and operates on large data sets. This paper presents another framework to implement the standard version of the AAM model. We suggest a distributed and parallel approach justified by the characteristics of the model and their potentialities. We introduce a schema for the representation of the overall model and we study of operations that can be parallelized. This approach is intended to exploit the benefits build in the area of advanced image processing.

• 한국공작기계학회논문집
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• 제16권6호
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• pp.110-116
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• 2007

This paper presents a new technique to implement the real-time recognition for shapes and model number of parts based on an active vision approach. The main focus of this paper is to apply a technique of 3D object recognition for non-contacting inspection of the shape and the external form state of precision parts based on the pattern recognition. In the field of computer vision, there have been many kinds of object recognition approaches. And most of these approaches focus on a method of recognition using a given input image (passive vision). It is, however, hard to recognize an object from model objects that have similar aspects each other. Recently, it has been perceived that an active vision is one of hopeful approaches to realize a robust object recognition system. The performance is illustrated by experiment for several parts and models.

• 한국정보통신학회논문지
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• 제18권10호
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• pp.2509-2515
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• 2014

본 논문에서는, 초고집적 CMOS를 위한 얕은 트랜치 격리로 기존의 수직 구조에서 내부 임계전압과 활성 영역의 스트레스 영향을 개선시키고자 한다. 이를 위해서 제안한 구조는 회자 모양의 얕은 트랜치 격리 구조이며, 기존 수직 구조와 제안한 구조에 대해서 전자농도 분포와 게이트 바이어스 대 에너지 밴드 형태, 열전자 스트레스와 열 손상의 유전 강화 전계를 분석 하고자 한다. 물리적 기본 모델들은 TCAD 툴을 이용하며, 집적화 소자들에 있어서 분석 조건은 주위 조건과 스트레스 인가이다. 분석 결과, 얕은 트랜치 격리 구조가 소자의 크기가 감소됨에 따라서 수동적인 전기적 기능이며, 트랜지스터 응용에서 제안한 회자 구조의 얕은 트랜치 격리 구조가 전기적 특성에서 전위차 전계와 포화 임계 전압이 높게 나타났으며, 활성영역에서 스트레스의 영향은 감소되었다. 이 결과 데이터를 바탕으로 제작한 소자의 결과 분석도 시뮬레이션 결과 데이터와 거의 동일하였다.