• Title/Summary/Keyword: Local feature

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Image Segmentation Based on Fusion of Range and Intensity Images (거리영상과 밝기영상의 fusion을 이용한 영상분할)

  • Chang, In-Su;Park, Rae-Hong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.9
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    • pp.95-103
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    • 1998
  • This paper proposes an image segmentation algorithm based on fusion of range and intensity images. Based on Bayesian theory, a priori knowledge is encoded by the Markov random field (MRF). A maximum a posteriori (MAP) estimator is constructed using the features extracted from range and intensity images. Objects are approximated by local planar surfaces in range images, and the parametric space is constructed with the surface parameters estimated pixelwise. In intensity images the ${\alpha}$-trimmed variance constructs the intensity feature. An image is segmented by optimizing the MAP estimator that is constructed using a likelihood function based on edge information. Computer simulation results shw that the proposed fusion algorithm effectively segments the images independentl of shadow, noise, and light-blurring.

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Environmental Fatigue Evaluation of APR1000 Reactor Vessel (APR1000 원자로용기의 환경피로 평가)

  • Kim, Jong Min;Kim, Yong Hwan
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.26 no.3
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    • pp.207-212
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    • 2013
  • APR1000(Advanced Power Reactor 1000) was developed to export 1000MW nuclear power plants by adding ADFs(Advanced Design Features) including 60 years design life, local frequency control operation, 0.3g SSE, etc. to OPR1000(Optimized Power Reactor 1000). In this paper, environmental fatigue analyses for the reactor vessel in APR1000 have been performed as per Reg. Guide 1.207. Outlet nozzle, which has a relatively high cumulative usage factor in the reactor vessel was evaluated and a structural integrity is maintained under the reactor coolant environment.

Bayesian estimation of kinematic parameters of disk galaxies in large HI galaxy surveys

  • Oh, Se-Heon;Staveley-Smith, Lister
    • The Bulletin of The Korean Astronomical Society
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    • v.41 no.2
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    • pp.62.2-62.2
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    • 2016
  • We present a newly developed algorithm based on a Bayesian method for 2D tilted-ring analysis of disk galaxies which operates on velocity fields. Compared to the conventional ones based on a chi-squared minimisation procedure, this new Bayesian-based algorithm less suffers from local minima of the model parameters even with high multi-modality of their posterior distributions. Moreover, the Bayesian analysis implemented via Markov Chain Monte Carlo (MCMC) sampling only requires broad ranges of posterior distributions of the parameters, which makes the fitting procedure fully automated. This feature is essential for performing kinematic analysis of an unprecedented number of resolved galaxies from the upcoming Square Kilometre Array (SKA) pathfinders' galaxy surveys. A standalone code, the so-called '2D Bayesian Automated Tilted-ring fitter' (2DBAT) that implements the Bayesian fits of 2D tilted-ring models is developed for deriving rotation curves of galaxies that are at least marginally resolved (> 3 beams across the semi-major axis) and moderately inclined (20 < i < 70 degree). The main layout of 2DBAT and its performance test are discussed using sample galaxies from Australia Telescope Compact Array (ATCA) observations as well as artificial data cubes built based on representative rotation curves of intermediate-mass and massive spiral galaxies.

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Modulator of surface plasmon polariton based cycle branch graphene waveguide

  • Zhu, Jun;Xu, Zhengjie;Xu, Wenju;Wei, Duqu
    • Carbon letters
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    • v.25
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    • pp.84-88
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    • 2018
  • At present, an important research area is the search for materials that are compatible with CMOS technology and achieve a satisfactory response rate and modulation efficiency. A strong local field of graphene surface plasmon polariton (SPP) can increase the interaction between light and graphene, reduce device size, and facilitate the integration of materials with CMOS. In this study, we design a new modulator of SPP-based cycle branch graphene waveguide. The structure comprises a primary waveguide of graphene-$LiNbO_3$-graphene, and a secondary cycle branch waveguide is etched on the surface of $LiNbO_3$. Part of the incident light in the primary waveguide enters the secondary waveguide, thus leading to a phase difference with the primary waveguide as reflected at the end of the branch and interaction coupling to enhance output light intensity. Through feature analysis, we discover that the area of the secondary waveguide shows significant localized fields and SPPs. Moreover, the cycle branch graphene waveguide can realize gain compensation, reduce transmission loss, and increase transmission distance. Numerical simulations show that the minimum effective mode field area is about $0.0130{\lambda}^2$, the gain coefficient is about $700cm^{-1}$, and the quality factor can reach 150. The structure can realize the mode field limits of deep subwavelength and achieve a good comprehensive performance.

CRF-Based Figure/Ground Segmentation with Pixel-Level Sparse Coding and Neighborhood Interactions

  • Zhang, Lihe;Piao, Yongri
    • Journal of information and communication convergence engineering
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    • v.13 no.3
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    • pp.205-214
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    • 2015
  • In this paper, we propose a new approach to learning a discriminative model for figure/ground segmentation by incorporating the bag-of-features and conditional random field (CRF) techniques. We advocate the use of image patches instead of superpixels as the basic processing unit. The latter has a homogeneous appearance and adheres to object boundaries, while an image patch often contains more discriminative information (e.g., local image structure) to distinguish its categories. We use pixel-level sparse coding to represent an image patch. With the proposed feature representation, the unary classifier achieves a considerable binary segmentation performance. Further, we integrate unary and pairwise potentials into the CRF model to refine the segmentation results. The pairwise potentials include color and texture potentials with neighborhood interactions, and an edge potential. High segmentation accuracy is demonstrated on three benchmark datasets: the Weizmann horse dataset, the VOC2006 cow dataset, and the MSRC multiclass dataset. Extensive experiments show that the proposed approach performs favorably against the state-of-the-art approaches.

Digital Image Encryption Method Using Interleaving and Random Shuffling (인터리빙과 랜덤 셔플링을 이용한 디지털 영상의 암호화 방법)

  • Lee Ji-Bum;Ko Hyung-Hwa
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.5C
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    • pp.497-502
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    • 2006
  • In this paper, we propose a digital image encryption method using adaptive interleaving and multiple random shuffling table to improve the existing encryption methods which use a fixed random shuffling table. In order to withstand the plaintext attack, at first, we propose a interleaving method that is adaptive to the local feature of image. Secondly, using the proposed interleaving only shuffling method and multiple shuffling method that is combined interleaving with existing random shuffling method, we encrypted image by shuffled the DPCM processed $8^*8$ blocks. Experimental results show that, the proposed algorithm is very robust to plaintext attack and there is no overhead bit.

Gaze Detection by Wearable Eye-Tracking and NIR LED-Based Head-Tracking Device Based on SVR

  • Cho, Chul Woo;Lee, Ji Woo;Shin, Kwang Yong;Lee, Eui Chul;Park, Kang Ryoung;Lee, Heekyung;Cha, Jihun
    • ETRI Journal
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    • v.34 no.4
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    • pp.542-552
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    • 2012
  • In this paper, a gaze estimation method is proposed for use with a large-sized display at a distance. Our research has the following four novelties: this is the first study on gaze-tracking for large-sized displays and large Z (viewing) distances; our gaze-tracking accuracy is not affected by head movements since the proposed method tracks the head by using a near infrared camera and an infrared light-emitting diode; the threshold for local binarization of the pupil area is adaptively determined by using a p-tile method based on circular edge detection irrespective of the eyelid or eyelash shadows; and accurate gaze position is calculated by using two support vector regressions without complicated calibrations for the camera, display, and user's eyes, in which the gaze positions and head movements are used as feature values. The root mean square error of gaze detection is calculated as $0.79^{\circ}$ for a 30-inch screen.

Effects of Duct Aspect Ratios on Heat/Mass Transfer With Discrete V-Shaped Ribs (쐐기형 단락요철이 설치된 덕트의 종횡비가 열/물질 전달에 미치는 영향)

  • Lee, Dong-Hyun;Rhee, Dong-Ho;Cho, Hyung-Hee
    • Proceedings of the KSME Conference
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    • 2003.04a
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    • pp.1453-1460
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    • 2003
  • The present study investigates the effects of rib arrangements and aspect ratios of a rectangular duct simulating the cooling passage of a gas turbine blade. Two different V-shaped rib configurations are tested with the aspect ratios (W/H) of 3 to 6.82. One is the continuous V-shaped rib configuration with $60^{\circ}$ attack angle, and the other is the discrete V-shaped rib configuration with $45^{\circ}$ attack angle. The square ribs with the pitch to height ratio of 10.0 are installed on the test section in a parallel arrangement for both rib configurations. Reynolds numbers based on the hydraulic diameter are changed from 10,000 to 30,000. A naphthalene sublimation method is used to measure local heat/mass transfer coefficients. For the continuous V-shaped rib configuration, two pairs of counter-rotating vortices are generated in a duct, and high transfer region is formed at the center of the ribbed walls of the duct. However, for the discrete V-shaped rib configuration with $45^{\circ}$ attack angle, complex secondary flow patterns are generated in the duct due to its geometric feature, and more uniform heat/mass transfer distributions are obtained for all tested cases

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Clothing Design of Korean Image for Cultural Prooducts -using the literary artist´s works- (문인화를 이용한 한국적 이미지의 문화상품용 의상디자인 개발)

  • 오현정;오선희;이귀례
    • Journal of the Korean Society of Costume
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    • v.53 no.5
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    • pp.13-22
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    • 2003
  • The purposes of this study are to develop a Korean image clothing design for cultural products by using the literary artist´s works and to satisfy the demand of the local self-government and of Gwangju ㆍChonnam area´s small and medium-sized companies. The image of traditional Korean clothing can be expressed with adjectives like Pure, plain, rhythmical, neatness, plentiful, and calm etc. These attributes are similar to the characteristics of the literary artist´s style, which is expressed as suggestive, animated, spatial, possibility of stationary, serene and still. The features of the traditional Korean clothing design can be described as ´The Beauty of Elegance´, ´The Beauty of Plainness´, ´The Beauty of Asymmetric Balance´ and ´The Beauty of rhythm´. It can be expressed in the modern fashion design, which is developed through the combination of the most important feature like ´The Beauty of Space´ in the literary artist´s style. At the time of production we tried to express spatial beauty and plentiful taste of the literary artist's style in the clothing design of Korean image for cultural products by considering the balance between them. Six works of the literary artist were selected which satisfied the purpose of the developed clothing design item. The results were nine clothing designs of Korean image, like a skirt suit made up of a blouse and a skirt, a pants suit made up of pants and a jacket, two evening dresses with a shawl, and also T-shirts and one-pieces etc.

Face Recognition using Non-negative Matrix Factorization and Learning Vector Quantization (비음수 행렬 분해와 학습 벡터 양자화를 이용한 얼굴 인식)

  • Jin, Donghan;Kang, Hyunchul
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.3
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    • pp.55-62
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    • 2017
  • Non-negative matrix factorization (NMF) is one of the typical parts-based representation in which images are expressed as a linear combination of basis vectors that show the lcoal features or objects in the images. In this paper, we represent face images using various NMF methods and recognize their face identities based on extracted features using a learning vector quantization. We analyzed the various NMF methods by comparing extracted basis vectors. Also we confirmed the availability of NMF to the face recognition by verification of recognition rate of the various NMF methods.