• 복식
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• 제52권1호
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• pp.103-115
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• 2002

The purpose of this study is understanding modern woman's various aesthetic values and aesthetic sense through observing expression aspects of gender images in the 1990s military fashion and analyzing their aesthetic characteristics and formative factors. Gender images in military fashion have expressed the masculine image of authoritative image and offensive image and offensive image, and the feminine image of conservative image and ostentatious image, sensual image. The authoritative image showed authority and dignity of military uniform by using the classic military uniform's image. This spoke for desire of women to rise their position. Heroism and androcentrism affected as its formation factor. The offensive image destroyed original dignified image of military uniform by that resistance to authoritative image and existing gender identity appeared as way-out form and deconstructive expression. Anti-establishment spirit, resistance to gender identity, and deconstructionism affected as its formation factor. The conservative image expressed military fashion only with slim and soft silhouette, curved line, color, and simple details by magnifying feminity. Fallen man's authority affected as its formation factor. The ostentatious image expressed military fashion with magnifying accessories such as gold button and belt by women who wanted to display ostentatiously their social position and charm. The aspiration for class of elite affected as its formation factor. The sensual image intended to show erotic voluptuous beauty of woman's body by indirect and direct body exposure. Narcissism, desire to show, and sexual amusement affected as its formation factor.

• 한국군사과학기술학회지
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• 제21권1호
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• pp.40-46
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• 2018

In order to successfully detect and identify underwater targets located on the seabed, unmanned surface vehicles (USVs) typically acquire acoustic signals with a side-scan sonar device and reconstruct information about the target from the processed images. As the quality of the side-scan sonar images acquired by USVs depends on the environment and operating parameters, using modeling and simulation techniques to design side-scan sonar devices can help optimize the reconstruction of the sonar images. In this work, we study a side-scan sonar design for use in USVs, that takes the movement of the platform into account. First, we constructed a simulated seabed environment with underwater targets, and specified the maneuvering conditions and sonar systems. We then generated the acoustic signals from the simulated environment using the sonar equation. Finally, we successfully imaged the simulated seabed environment using simple signal processing. Our results can be used to derive USV side-scan sonar design parameters, predict the resulting sonar images in various conditions, and as a basis for determining the optimal sonar parameters of the system.

• Current Optics and Photonics
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• 제5권6호
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• pp.686-698
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• 2021

A camouflaged encryption scheme based on Hadamard matrix and ghost imaging is proposed. In the process of the encryption, an orthogonal matrix is used as the projection pattern of ghost imaging to improve the definition of the reconstructed images. The ciphertext of the secret image is constrained to the camouflaged image. The key of the camouflaged image is obtained by the method of sparse decomposition by principal component orthogonal basis and the constrained ciphertext. The information of the secret image is hidden into the information of the camouflaged image which can improve the security of the system. In the decryption process, the authorized user needs to extract the key of the secret image according to the obtained random sequences. The real encrypted information can be obtained. Otherwise, the obtained image is the camouflaged image. In order to verify the feasibility, security and robustness of the encryption system, binary images and gray-scale images are selected for simulation and experiment. The results show that the proposed encryption system simplifies the calculation process, and also improves the definition of the reconstructed images and the security of the encryption system.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.376-379
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• 2006

A numerous oil slicks of natural origin were revealed in the southwest (SW) part of Caspian Sea by the synthetic aperture radar (SAR) images acquired by Envisat satellite in 2003-2004. On the basis of computer processing, visual analysis of SAR images and comparisons with bathymetry, geophysical and seismic data in geographic information system (GIS), a link between these slicks and unloading of liquid hydrocarbons in the SW Caspian is established. Oil slicks are basically concentrated above domes of local geological formations of the sedimentary cover. In total more than 90 seeps and mud volcanoes having a repeating regime and representing an active type were identified; they are distributed across the SW Azerbaijan and West Iranian sectors. Periodical occurrence of slicks can reflect alternation of mud volcanism pulses forced by intensive seismicity with the quiet periods. Seepage rate of oil in the SW part of the Caspian Sea according to SAR images is estimated to be up to 16,000 metric tons per year. The importance of unloading of oils on hydrochemistry and ecological conditions of the Caspian Sea is demonstrated. Conclusion is done that the Envisat SAR to be an excellent tool for studying oil seeps through observation oil slicks floating on the sea surface.

• 제어로봇시스템학회논문지
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• 제22권3호
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• pp.241-246
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• 2016

Nowadays many people have an interest in facial expression and the behavior of people. These are human-robot interaction (HRI) researchers utilize digital image processing, pattern recognition and machine learning for their studies. Facial feature point detector algorithms are very important for face recognition, gaze tracking, expression, and emotion recognition. In this paper, a cascade facial feature point detector is used for finding facial feature points such as the eyes, nose and mouth. However, the detector has difficulty extracting the feature points from several images, because images have different conditions such as size, color, brightness, etc. Therefore, in this paper, we propose an algorithm using a modified cascade facial feature point detector using a convolutional neural network. The structure of the convolution neural network is based on LeNet-5 of Yann LeCun. For input data of the convolutional neural network, outputs from a cascade facial feature point detector that have color and gray images were used. The images were resized to $32{\times}32$. In addition, the gray images were made into the YUV format. The gray and color images are the basis for the convolution neural network. Then, we classified about 1,200 testing images that show subjects. This research found that the proposed method is more accurate than a cascade facial feature point detector, because the algorithm provides modified results from the cascade facial feature point detector.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.322-323
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• 2002

Partial volume averaging effect of PET data influences on the accuracy of quantitative measurements of regional brain metabolism because spatial resolution of PET is limited. The purpose of this study was to evaluate the accuracy of partial volume correction carried out on $^{18}$ F-PET images using Hoffman brain phantom. $^{18}$ F-PET Hoffman phantom images were co-registered to MR slices of the same phantom. All the MR slices of the phantom were then segmented to be binary images. Each of these binary images was convolved in 2 dimensions with the spatial resolution of the PET. The original PET images were then divided by the smoothed binary images in slice-by-slice, voxel-by-voxel basis resulting in larger PET image volume in size. This enlarged partial volume corrected PET image volume was multiplied by original binary image volume to exclude extracortical region. The evaluation of partial volume corrected PET image volume was performed by region of interests (ROI) analysis applying ROIs, which were drawn on cortical regions of the original MR image slices, to corrected and original PET image volume. From the ROI analysis, range of regional mean values increases of partial volume corrected PET images was 4 to 14%, and average increase for all the ROIs was about 10% in this phantom study. Hoffman brain phantom study was useful for the objective evaluation of the partial volume correction method. This MR-based correction method would be applicable to patients in the. quantitative analysis of FDG-PET studies.

• 한국통신학회논문지
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• 제19권11호
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• pp.2106-2115
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• 1994

영상의 구조인식과 같은 고단계 처리 과정의 성능은 앞단에서 검출된 경계 성분의 정확성에 크게 의존하는 바. 정확한 경계검출의 문제는 컴퓨터 버전 분야에서 가장 기본이 되는 연구주제로서 많이 수행되어 왔다. 그러나 검출 및 국소화 기능 사이에 근본적으로 존재하는 상충관계를 해결할 수 있는 안정적이면서도 영상의 통계적 특성에 무관한 효율적인 경계검출 알고리즘의 개발은 아직도 남아있는 연구과제이다. 본 논문에서는 이러한 문제점을 해결하기 위하여 경계검출을 위한 전처리 과정으로서 B-spline 기저 함수를 이용한 경계 보존 면 평활화 과정을 수행함으로써 단순한 저역통과 필터의 적용으로 발생되는 경계 성분의 이동이나 소멸과 같은 효과를 억제하여, 주변 파라미터의 변동에 민감하지 않은 안정적인 알고리즘을 제안하였다. 이를 위해 크기변화 및 차영상을 이용한 경계강조 및 보간을 아울러 수행하였다. 최종적으로 경계성분 검출을 위해 Marr와 Hildreth가 제안한 Laplacian of Gaussian(LOG) 연산자를 이용하였다. $256\times256$ 크기의 실험영상에 대한 모의실험 결과, 전처리과정을 거치지 않고 LOG 연산자만을 사용한 경우와 비교해 볼때. 제안한 방법은 평활화 필터의 크기, 즉. 공간상수값($\sigma$=0.9, 1.1, 1.3) 및 영교차점 검출 과정에서 사용되는 임계치(t=10, 20)의 변화에 대해 거의 영향을 받지 않는 안정된 알고리즘임을 확인하였다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제29권3호
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• pp.145-155
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• 2002

내용 기반 영상 검색에서 대부분의 기존 방법들은 서로 다른 특징들 사이의 선형 관계를 가정하고 또 사용자가 직접 각 특징의 가중치를 설정하도록 한다 허나 특징들 사이의 관계가 선형적으로 가정된 하에서는 고차원의 개념과 인간의 지각 주관성을 충분히 표현할 수 없는 단점이 있다. 본 논문에서는 신경망에 기반한 영상 검색 모델이 제안된다. 이는 RBFN을 이용한 내용 기반 영상 검색 기법과 인간컴퓨터 상호작용의 접근 방법을 기반으로 구축되었다. RBFN을 이용하여 특징들 사이의 비선형적 관계를 추출해낼 수 있고 사용자가 처음에 질의 영상을 선택하고 관련성 피드백을 통하여 점차적으로 목표 영상을 찾아나가도록 함으로써 영상의 비교를 더 정확하게 할 수 있다. 실험은 145개의 클래스로 구분되며 1,015개의 영상을 포함하는 데이타베이스를 사용하여 재생과 정도를 계산하였다. 실험 결과는 제안된 방법의 재생과 정도가 각각 93.45%과 80.61%로서, 기존의 선형 결합 방법이나 순위 기반 방법 그리고 역전파 알고리즘에 기반한 방법보다 더 뛰어난 검색 성능을 지님을 보여준다.

• 복식
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• 제53권4호
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• pp.49-69
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• 2003

The purpose of the study is to develop the competitive swimming suit design with Korean traditional images. which excels in dimension of functionality, aesthetics, and symbolism. To accomplish this study, first. a theoretical examination about Korean image was added, on the basis of the practical research about professional swimmers' preferences as well as the theoretical research about the history of swimming suits and the qualifications of competitive swimming suits in the prior study. Next, practical designing was performed to achieve the creative designs according to Lamb & Kallal's design process. and the superiority of the newly designed swimming suits was evaluated by using Grant's alpha-beta model. The results of this study can be summarized as follows : First. in the problem apprehension stage. the need for swimming suit designs with Korean traditional images for professional swimmers was acknowledged, and three major criteria. which are functionality, aesthetics. and symbolism has been verified. Second. in the preliminary brainstorming stage, considerable amounts of data for the design concept considering the criteria above have been gathered. The athletic one-piece for women and the brief for men in style and nylon/lycra in fabric were used in the aspect of functionality. And the S Korean traditional colors in color and Tae-guk motive and others in pattern were selected to apply Korean traditional images in the aspects of aesthetics and symbolism. Finally, the 13 series of creative designs with 4 themes( l17pieces in total) have been suggested. Third, in the design improvement stage. after the preference to each design was surveyed, reformation of the designs was arranged on the basis of the results. Fourth, in the prototyping stage. the 17 actual prototypes, including 13 pieces for women and 4 pieces for men were produced. Fifth. in the evaluation stage. the evaluation procedure using Grant's alpha-beta model was performed. As a result, the newly designed swimming suits were rated above other existing ones in all three aspects of functionality, aesthetics, and symbolism.

• 한국정보통신학회논문지
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• 제23권6호
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• pp.682-689
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• 2019

부분 기반 영상 표현(part-based image representation)에서는 영상의 부분적인 모습을 기저 벡터로 표현하고 기저 벡터의 선형 조합으로 영상을 분해하며, 이 때 기저 벡터의 계수가 곧 물체의 부분적인 특징을 의미하게 된다. 본 논문에는 부분 기반 영상 표현 기법인 비음수 행렬 분해(non-negative matrix factorization, NMF)를 이용하여 얼굴 영상을 표현하고 신경망 기법을 적용하여 가려진 얼굴을 인식하는 얼굴 인식을 제안한다. 표준 비음수 행렬 분해, 투영 경사 비음수 행렬 분해, 직교 비음수 행렬 분해를 이용하여 얼굴 영상을 표현하였고, 각 기법의 성능을 비교하였다. 인식기로는 학습벡터양자화 신경망을 사용하였으며, 인식기에서의 거리 척도로는 유클리디언 거리를 사용하였다. 실험 결과, 전통적인 얼굴 인식 방법에 비하여 제안한 기법이 가려진 얼굴 인식에 보다 강인함을 보인다.