• 제목/요약/키워드: Local feature

검색결과 933건 처리시간 0.023초

램프의 완전 선명화를 이용한 에지 검출기 (An Edge Detector by Using Perfect Sharpening of Ramps)

  • 이종구;유철중;장옥배
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제34권11호
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    • pp.961-970
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    • 2007
  • 국소적 미분 연산자를 이용한 대개의 에지 검출 방법을 사용하면 검출된 에지의 폭이 불균일하게 되거나, 확대된 영상에서 에지의 일부를 검출하지 못한다. 캠프 에지의 엄격하게 단조적인 자기 분포구간을 단순 계단 함수에 대응시키는 램프 에지의 완전 선명화 사상을 이용하면 자기분포의 비국소적 속성이 반영되는 변형된 미분이 도입되고, 이를 이용하면 다양한 에지 폭의 변화에 효율적으로 대응할 수 있는 에지 검출기를 구현할 수 있다. 본 논문에서는 MADD를 사용하여 형상의 확대나 다양한 에지 폭의 변화에 안정적으로 동작하는 검출기를 개발하였다. 기존의 알고리즘과 비교하여 본 결과 제안한 알고리즘의 우수성을 확인할 수 있었다.

LBP and DWT Based Fragile Watermarking for Image Authentication

  • Wang, Chengyou;Zhang, Heng;Zhou, Xiao
    • Journal of Information Processing Systems
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    • 제14권3호
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    • pp.666-679
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    • 2018
  • The discrete wavelet transform (DWT) has good multi-resolution decomposition characteristic and its low frequency component contains the basic information of an image. Based on this, a fragile watermarking using the local binary pattern (LBP) and DWT is proposed for image authentication. In this method, the LBP pattern of low frequency wavelet coefficients is adopted as a feature watermark, and it is inserted into the least significant bit (LSB) of the maximum pixel value in each block of host image. To guarantee the safety of the proposed algorithm, the logistic map is applied to encrypt the watermark. In addition, the locations of the maximum pixel values are stored in advance, which will be used to extract watermark on the receiving side. Due to the use of DWT, the watermarked image generated by the proposed scheme has high visual quality. Compared with other state-of-the-art watermarking methods, experimental results manifest that the proposed algorithm not only has lower watermark payloads, but also achieves good performance in tamper identification and localization for various attacks.

A Theory on Phase Behaviors of Diblock Copolymer/Homopolymer Blends

  • 윤경섭;박형석
    • Bulletin of the Korean Chemical Society
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    • 제16권9호
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    • pp.873-885
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    • 1995
  • The local structural and thermodynamical properties of blends A-B/H of a diblock copolymer A-B and a homopolymer H are studied using the polymer reference interaction site model (RISM) integral equation theory with the mean-spherical approximation closure. The random phase approximation (RPA)-like static scattering function is derived and the interaction parameter is obtained to investigate the phase transition behaviors in A-B/H blends effectively. The dependences of the microscopic interaction parameter and the macrophase-microphase separation on temperature, molecular weight, block composition and segment size ratio of the diblock copolymer, density, and concentration of the added homopolymer, are investigated numerically within the framework of Gaussian chain statistics. The numerical calculations of site-site interchain pair correlation functions are performed to see the local structures for the model blends. The calculated phase diagrams for A-B/H blends from the polymer RISM theory are compared with results by the RPA model and transmission electron microscopy (TEM). Our extended formal version shows the different feature from RPA in the microscopic phase separation behavior, but shows the consistency with TEM qualitatively. Scaling relationships of scattering peak, interaction parameter, and temperature at the microphase separation are obtained for the molecular weight of diblock copolymer. They are compared with the recent data by small-angle neutron scattering measurements.

Adaptive Cooperative Spectrum Sensing Based on SNR Estimation in Cognitive Radio Networks

  • Ni, Shuiping;Chang, Huigang;Xu, Yuping
    • Journal of Information Processing Systems
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    • 제15권3호
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    • pp.604-615
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    • 2019
  • Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and other unfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracy and reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimated signal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED) is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a better sensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNR with low complexity. The local sensing node transmits the perceived results through the control channel to the fusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth is effectively saved. Simulation results show that the proposed scheme can effectively improve the system detection probability, shorten the average sensing time, and has better robustness without largely increasing the costs of sensing system.

텍스처 기술자들을 이용한 이질적 얼굴 인식 시스템 (Heterogeneous Face Recognition Using Texture feature descriptors)

  • 배한별;이상윤
    • 한국정보전자통신기술학회논문지
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    • 제14권3호
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    • pp.208-214
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    • 2021
  • 최근 많은 지능형 보안 시나리오 및 범죄수사에서는 사진이 아닌 얼굴 영상과 다수의 정면 사진과의 매칭을 요구한다. 기존의 얼굴 인식 시스템은 이러한 요구를 충분히 충족시킬 수 없다. 본 논문에서는 동일 인물의 스케치와 사진 간의 양식 차이를 줄임으로써, 이질적 얼굴 인식 시스템의 성능을 향상시키는 알고리즘을 제안한다. 제안하는 알고리즘은 텍스처 기술자들(그레이 레벨 동시 발생 행렬, 멀티스케일 지역 이진 패턴)을 통하여 영상의 텍스처 특징들을 각각 추출하고, 이를 바탕으로 고유특징 정규화 및 추출기법을 통해 변환 행렬을 생성하게 된다. 이렇게 생성된 벡터들 간 계산된 스코어 값은 스코어 정규화 방식들을 통하여 최종적으로 스케치 영상의 신원을 인식하게 된다.

Generative Adversarial Networks for single image with high quality image

  • Zhao, Liquan;Zhang, Yupeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권12호
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    • pp.4326-4344
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    • 2021
  • The SinGAN is one of generative adversarial networks that can be trained on a single nature image. It has poor ability to learn more global features from nature image, and losses much local detail information when it generates arbitrary size image sample. To solve the problem, a non-linear function is firstly proposed to control downsampling ratio that is ratio between the size of current image and the size of next downsampled image, to increase the ratio with increase of the number of downsampling. This makes the low-resolution images obtained by downsampling have higher proportion in all downsampled images. The low-resolution images usually contain much global information. Therefore, it can help the model to learn more global feature information from downsampled images. Secondly, the attention mechanism is introduced to the generative network to increase the weight of effective image information. This can make the network learn more local details. Besides, in order to make the output image more natural, the TVLoss function is introduced to the loss function of SinGAN, to reduce the difference between adjacent pixels and smear phenomenon for the output image. A large number of experimental results show that our proposed model has better performance than other methods in generating random samples with fixed size and arbitrary size, image harmonization and editing.

Deep Local Multi-level Feature Aggregation Based High-speed Train Image Matching

  • Li, Jun;Li, Xiang;Wei, Yifei;Wang, Xiaojun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권5호
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    • pp.1597-1610
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    • 2022
  • At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

도시숲 조성 및 관리를 위한 도시숲 유형화 및 적용방안 (Classification of Urban Forest Types and its Application Methods for Forests Creation and Management)

  • 이동근;김은영;송원경;박찬;최혜영
    • 한국환경복원기술학회지
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    • 제12권5호
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    • pp.101-109
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    • 2009
  • There are increasing needs about creation and sustainable management of urban forest for environmental conservation and recreational service for citizen. However, it is difficult for local governments to create or manage urban forest in recreational or conservational way. The purpose of this study is to classify the urban forest types by considering its geographical feature, biological and sociological characteristics in order to suggest a guide to local governments about effective creation or management of urban forest. In this study, we extracted common characteristics of the selected five indicators. Factors about urban forest are divided into two groups. Factors were named according to the variables as 'Urban Forest Naturalness', and 'High Accessibility and Disturbed by Human.' In addition, we classified urban forests into four types in this study. The type I of urban forest is a large forest and has high naturalness such as Mt. Bukhan and Mt. Gwanak. The type II is fragmented to large forests by developmental projects. The type III is flat and has high accessibility such as forest behind Seonjeongneung. The type IV is located near residential area such as Mt. Ansan, Mt. Inwang and Mt. Bonghwa. It is possible to set up recreational area for citizens and ecological networks for species by the research of the urban forest type. The results of the study, classification of urban forest types and its application, contribute to provide a guide for local governments to create or manage urban forests effectively.

실시간 얼굴 검출 시스템의 하드웨어 IP 구현 (Implementation for Hardware IP of Real-time Face Detection System)

  • 장준영;육지홍;조호상;강봉순
    • 한국정보통신학회논문지
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    • 제15권11호
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    • pp.2365-2373
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    • 2011
  • 본 논문은 고속화, 소형화 및 저전력을 요구하는 모바일 기기 및 디지털 카메라에 알맞은 실시간 얼굴 검출 하드웨어 IP(Intellectual Property)를 제안한다. 제안한 얼굴 검출 시스템은 검출 성능의 주요 원인인 조명 변화나 얼굴 크기, 다양한 얼굴 각도에 강인한 얼굴 검출을 수행한다. 입력 영상에 대해 조명 변화에 강인한 특성을 가지는 LBP(Local Binary Pattern) 변환을 거치고 Adaboost 알고리즘을 이용하여 다양한 얼굴 각도에 대해 미리 학습시킨 얼굴 특징 정보를 바탕으로 얼굴을 검출한다. 입력 영상 QVGA($320{\times}240$) 크기에서 최대 36개의 얼굴 검출 가능하며 Verilog-HDL을 사용하여 하드웨어로 설계하였다. 또한 FPGA 검증을 위해 Xilinx사의 Virtex5 XC5VLX330 FPGA 보드와 HD급 CMOS 이미지 센서(CIS)를 사용하여 하드웨어 구현을 검증하였다.

X-ray absorption spectroscopic study of MgFe2O4 nanoparticles

  • Singh, Jitendra Pal;Lim, Weon Cheol;Song, Jonghan;Kim, Joon Kon;Chae, Keun Hwa
    • 한국진공학회:학술대회논문집
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    • 한국진공학회 2015년도 제49회 하계 정기학술대회 초록집
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    • pp.230.2-230.2
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    • 2015
  • Nanoparticles of magnesium ferrite are used as a heterogeneous catalyst, humidity sensor, oxygen sensor and cure of local hyperthermia. These applications usually utilize the magnetic behavior of these nanoparticles. Moreover, magnetic properties of nanoferrites exhibit rather complex behavior compared to bulk ferrite. The magnetic properties of ferrites are complicated by spins at vortices, surface spins. Reports till date indicate strong dependency on the structural parameters, oxidation state of metal ions and their presence in octahedral and tetrahedral environment. Thus we have carried out investigation on magnesium ferrite nanoparticles in order to study coordination, oxidation state and structural distortion. For present work, magnesium ferrite nanoparticles were synthesized using nitrates of metal ions and citric acid. Fe L-edge spectra measured for these nanoparticles shows attributes of $Fe^{3+}$ in high spin state. Moreover O K-edge spectra for these nanoparticles exhibit spectral features that arises due to unoccupied states of O 2p character hybridized with metal ions. Mg K-edge spectra shows spectral features at 1304, 1307, 1311 and 1324 eV for nanoparticles obtained after annealing at 400, 500, 600, 800, 1000, and $1200^{\circ}C$. Apart from this, spectra for precursor and nanoparticles obtained at $300^{\circ}C$ exhibit a broad peak centered around 1305 eV. A shoulde rlike structure is present at 1301 eV in spectra for precursor. This feature does not appear after annealing. After annealing a small kink appear at ~1297 eV in Mg K-edge spectra for all nanoparticles. This indicates changes in local electronic structure during annealing of precursor. Observed behavior of change in local electronic structure will be discussed on the basis of existing theories.

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