• 전자공학회논문지
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• 제51권6호
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• pp.132-142
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• 2014

근래에 고령운전자의 증가와 다양한 차량용 멀티미디어 기기의 등장으로 운전 중 운전자의 시각적 주의 결핍 및 분산되어 교통신호등 오인식으로 인해 교통사고가 증가하고 있는 상황이다. 이를 보완하기 위해 일반적인 교통신호등 검출연구들은 색상 임계치, 템플릿 매칭, 학습기 기반 등의 방안이 제시 되었으나 색상 임계치의 경우 시내 도로와 같이 복잡한 배경과 주위 환경변화에 강인하지 못하고, 야간 시간대의 경우 템플릿 및 학습기 기반의 검출방안의 경우 그 인식도가 떨어지는 문제점이 존재한다. 따라서 제안한 방안에서는 교통신호등의 구조적인 형태 정보(모양, 밝기, 대비, 색상 등)을 기반 한 시각적 주의 영역과 spot-lights 영역 검출을 통해 복잡한 시내 도로 환경에서 교통신호등을 검출하는 방안을 제안한다. 교통신호등은 운전자의 시인성을 높일 수 있는 위치에 설치되고 또한 구조적인 고유한 형태와 색상을 지니고 있는 특징들을 이용하여 교통신호등을 검출한다. 제안한 방안에서는 입력된 칼라영상에서 특징정보들 간의 다차원 가우시안 파라미드 영상들을 생성하고 각 영상들 간의 대비차이 계산하여 현저하게 두드러진 영역들을 검출하고, 밝기 영상에서 주위 영역과 현저하게 밝은 spot-lights 영역들을 검출한다. 그리고 검출된 두 영역들의 모양과 색상 분석을 통해 교통신호등을 검출한다. 제안한 방법을 다양한 시간대와 시내 도로에서 실험한 결과, 교통신호등 검출률은 83.2%이고 프레임 당 처리 시간은 0.68초이다. 이것을 통해 사후판독 기능이 차량 영상기록장치에 결합한 안전운전 지원시스템으로 제안한 방안이 유용하게 적용될 수 있음을 알 수 있다.

• 한국정보전자통신기술학회논문지
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• 제12권6호
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• pp.629-635
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• 2019

여러 분야에서 사용되는 이미지 분류를 위한 딥러닝(Deep Learning) 모델은 오류 역전파 방법을 통해 미분을 구현하고 미분 값을 통해 예측 상의 오류를 학습한다. 엄청난 계산량을 향상된 계산 능력으로 해결하여, 복잡하게 설계된 모델에서도 파라미터의 전역 (혹은 국소) 최적점을 찾을 수 있다는 것이 장점이다. 하지만 정교하게 계산된 데이터를 만들어내면 이 딥러닝 모델을 '속여' 모델의 예측 정확도와 같은 성능을 저하시킬 수 있다. 이렇게 생성된 적대적 사례는 딥러닝을 저해할 수 있을 뿐 아니라, 사람의 눈으로는 쉽게 발견할 수 없도록 정교하게 계산되어 있다. 본 연구에서는 임의의 잡음 신호를 추가하는 방법을 통해 적대적으로 생성된 이미지 데이터셋을 탐지하는 방안을 제안한다. 임의의 잡음 신호를 추가하였을 때 일반적인 데이터셋은 예측 정확도가 거의 변하지 않는 반면, 적대적 데이터셋의 예측 정확도는 크게 변한다는 특성을 이용한다. 실험은 공격 기법(FGSM, Saliency Map)과 잡음 신호의 세기 수준(픽셀 최댓값 255 기준 0-19) 두 가지 변수를 독립 변수로 설정하고 임의의 잡음 신호를 추가하였을 때의 예측 정확도 차이를 종속 변수로 설정하여 시뮬레이션을 진행하였다. 각 변수별로 일반적 데이터셋과 적대적 데이터셋을 구분하는 탐지 역치를 도출하였으며, 이 탐지 역치를 통해 적대적 데이터셋을 탐지할 수 있었다.

• 영어어문교육
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• 제17권2호
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• pp.219-245
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• 2011

This case study aims to investigate how a primary English teacher's professional development was pursued through novice teacher mentoring after the six-month intensive in-service teacher training program(IIETTP). The teacher was involved in mentoring two novice teachers working at the same school. They observed each other's classes and exchanged their views on the classes, focusing on areas to be improved. The observation was done within a framework that consisted of pre-, during- and post-observation sessions. Data was gathered through retrospective entries kept after the post-observation meetings. The entries were categorized according to their saliency, frequency and recurring patterns identified. The findings reveal that learning from the training course could be applied professionally and could serve to bridge the gap between training and teaching. It is also shown that the mentee teachers' professional development was enhanced and the mentor teacher herself benefited from the collaborative learning process involved with working with the novice teachers. Some suggestions are made for the effective implementation of school-based teacher development programs after the IIETTP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4386-4404
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• 2016

Most existing salient object detection algorithms commonly employed segmentation techniques to eliminate background noise and reduce computation by treating each segment as a processing unit. However, individual small segments provide little information about global contents. Such schemes have limited capability on modeling global perceptual phenomena. In this paper, a novel salient object detection algorithm is proposed based on region merging. An adaptive-based merging scheme is developed to reassemble regions based on their color dissimilarities. The merging strategy can be described as that a region R is merged with its adjacent region Q if Q has the lowest dissimilarity with Q among all Q's adjacent regions. To guide the merging process, superpixels that located at the boundary of the image are treated as the seeds. However, it is possible for a boundary in the input image to be occupied by the foreground object. To avoid this case, we optimize the boundary influences by locating and eliminating erroneous boundaries before the region merging. We show that even though three simple region saliency measurements are adopted for each region, encouraging performance can be obtained. Experiments on four benchmark datasets including MSRA-B, SOD, SED and iCoSeg show the proposed method results in uniform object enhancement and achieve state-of-the-art performance by comparing with nine existing methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.588-590
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• 1994

This paper describes current controlled PWM technique of IPM synchronous motors for a wide variety of speed control applications. The IPM synchronous motors have a saliency, in which the q-axis inductance is larger than the d-axis inductance. As a consequence, there exists a reluctance torque component Thus when this component is added to the torque component produced by the stator currents and the air-gap flux, IPM motor drives are readily applicable where full torque Is required up to full or base speed. They are however limited in their ability to operate in the power limited regime where the available torque is reduced as the speed is increased above its base value. This paper reviews the operation of the IPMSM drives when they are constrained to be within the permissible envelope of maximum inverter voltage and current to produce the rated power and to provide this with the highest attainable rotor speed. The wide variety of speed control strategy is analyzed and the performance is investigated by the computer simulation using actual parameters of a drive system. Simulation results are given and discussed.

• 전기학회논문지
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• 제62권10호
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• pp.1425-1435
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• 2013

The useful method for determining parameters of weighting functions used to design the $H_{\infty}$ current controller for attenuating the current ripple due to saliencies which SPMSM(Surface Permanent Magnet Synchronous Motor) also incorporates is described. To analyze the effect, the current ripple due to the structural and the saturation saliencies, the SPMSM model with nonlinear inductance function depending on the two independent variables, rotor position and stator current is simulated. After analysis, parameters of the weighting functions for $H_{\infty}$ current controller is selected to satisfy the robust stability, robust performance and specific performance in time and frequency domain by using the PSO(Particle Swarm Optimization) algorithm in the linear SPMSM model. Especially, the robust performance is proved that the selected weighting functions play a role in reducing the current ripple caused by the saliencies of SPMSM at the desired frequency range by the simple experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.272-287
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• 2016

Recently, various and effective contrast based salient object detection models to focus on a single target have been proposed. However, there is a lack of research on detection of multiple objects, and also it is a more challenging task than single target process. In the multiple target problem, we are confronted by new difficulties caused by distinct difference between properties of objects. The characteristic of existing models depending on the global maximum distribution of data point would become a drawback for detection of multiple objects. In this paper, by analyzing limitations of the existing methods, we have devised three main processes to detect multiple salient objects. In the first stage, regional features are extracted from over-segmented regions. In the second stage, the regional features are categorized into homogeneous cluster using the mean-shift algorithm with the kernel function having various sizes. In the final stage, we compute saliency scores of the categorized regions using only spatial features without the contrast features, and then all scores are integrated for the final salient regions. In the experimental results, the scheme achieved superior detection accuracy for the SED2 and MSRA-ASD benchmarks with both a higher precision and better recall than state-of-the-art approaches. Especially, given multiple objects having different properties, our model significantly outperforms all existing models.

• IEIE Transactions on Smart Processing and Computing
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• 제6권4호
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• pp.229-236
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• 2017

This paper presents an efficient object-based color image-retrieval algorithm that is suitable for the classification and retrieval of images from small to mid-scale datasets, such as images in PCs, tablets, phones, and cameras. The proposed method first finds salient regions by using regional feature vectors, and also finds several dominant colors in each region. Then, each salient region is partitioned into small sub-blocks, which are assigned 1 or 0 with respect to the number of pixels corresponding to a dominant color in the sub-block. This gives a binary map for the dominant color, and this process is repeated for the predefined number of dominant colors. Finally, we have several binary maps, each of which corresponds to a dominant color in a salient region. Hence, the binary maps represent the spatial distribution of the dominant colors in the salient region, and the union (OR operation) of the maps can describe the approximate shapes of salient objects. Also proposed in this paper is a matching method that uses these binary maps and which needs very few computations, because most operations are binary. Experiments on widely used color image databases show that the proposed method performs better than state-of-the-art and previous color-based methods.

• Journal of Power Electronics
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• 제11권4호
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• pp.464-470
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• 2011

In this paper, the feasibility of applying a position sensorless control technique to hybrid electric vehicles (HEVs) is practically evaluated. The proposed position estimator has a straightforward structure with properties that combines the model and the saliency tracking-based rotor position estimation for interior permanent magnet synchronous motors (IPMSMs). The proposed method can be used in the event of sensor loss or sensor recovery to sustain continuity of operations. The developed system takes into account the estimated position transition between two distinct sensorless methods. The transition is enhanced by introducing a synchronized transition algorithm based on a single tracking observer. Extensive experimental results are presented to verify the principles and show a reliable estimation performance over the entire speed range including standstill under 150% load conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권3호
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• pp.539-557
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• 2013

A novel multifocus image fusion algorithm based on NSCT is proposed in this paper. In order to not only attain the image focusing properties and more visual information in the fused image, but also sensitive to the human visual perception, a local multidirection variance (LEOV) fusion rule is proposed for lowpass subband coefficient. In order to introduce more visual saliency, a modified local contrast is defined. In addition, according to the feature of distribution of highpass subband coefficients, a direction vector is proposed to constrain the modified local contrast and construct the new fusion rule for highpass subband coefficients selection The NSCT is a flexible multiscale, multidirection, and shift-invariant tool for image decomposition, which can be implemented via the atrous algorithm. The proposed fusion algorithm based on NSCT not only can prevent artifacts and erroneous from introducing into the fused image, but also can eliminate 'block effect' and 'frequency aliasing' phenomenon. Experimental results show that the proposed method achieved better fusion results than wavelet-based and CT-based fusion method in contrast and clarity.