• Title/Summary/Keyword: 비 선형 매핑

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Tone Mapping Method using Non-linear Dynamic Range Normalization for High Dynamic Range Images (HDR 영상을 위한 비선형 동적영역 정규화를 이용한 톤 매핑 기법)

  • Kim, Beom-Yong;Hwang, Bo-Hyun;Yun, Jong-Ho;Choi, Myung-Ryul
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.851-852
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    • 2008
  • In this paper, we propose a tone mapping method using Non-linear Dynamic Range Normalization (NDRN) for High Dynamic Range (HDR) images. HDR images are not suitable for commercial display devices because dynamic range of HDR images do not match with one of Low Dynamic Range (LDR) display devices. To reproduce a tone of HDR images for LDR displays, tone mapping methods have been proposed such as local and global tone mapping. We introduce NDRN to locate mean of HDR images at the center of LDR. NDRN preserves the details for highlight and shadow. By suppressing the significant luminance change in tone mapping, naturalness of original image can be also preserved. The experimental results show that the proposed method preserves details and naturalness of original images.

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Color Enhanced Method in Digital PDP TV Using Nonlinear Shortest Distance Mapping Algorithm (비선형적 최단거리 매핑 알고리즘을 이용한 PDP칼라 특성 보정 방법)

  • 허태욱;김재철;조맹섭
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.255-258
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    • 2002
  • Recently, Digital TV viewer have been replacing cathode ray tubes (CRT) with Plasma display panel(PDP). But the chromaticity of the primaries are dependent on RGB input signals. And the colorimetry of PDP changes with gray scale and has a poor performance in color reproduction. In this paper we propose the enhanced algorithm of color reproduction considering nonlinear gamut mapping algorithm. In order to test performance of this algorithm we use the sample colors. As a result of experiments, it was confirmed that the color difference of the digital PDP using the proposed algorithm was considerably reduced.

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Dimension Reduction Method of Speech Feature Vector for Real-Time Adaptation of Voice Activity Detection (음성구간 검출기의 실시간 적응화를 위한 음성 특징벡터의 차원 축소 방법)

  • Park Jin-Young;Lee Kwang-Seok;Hur Kang-In
    • Journal of the Institute of Convergence Signal Processing
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    • v.7 no.3
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    • pp.116-121
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    • 2006
  • In this paper, we propose the dimension reduction method of multi-dimension speech feature vector for real-time adaptation procedure in various noisy environments. This method which reduces dimensions non-linearly to map the likelihood of speech feature vector and noise feature vector. The LRT(Likelihood Ratio Test) is used for classifying speech and non-speech. The results of implementation are similar to multi-dimensional speech feature vector. The results of speech recognition implementation of detected speech data are also similar to multi-dimensional(10-order dimensional MFCC(Mel-Frequency Cepstral Coefficient)) speech feature vector.

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HMM-based Upper-body Gesture Recognition for Virtual Playing Ground Interface (가상 놀이 공간 인터페이스를 위한 HMM 기반 상반신 제스처 인식)

  • Park, Jae-Wan;Oh, Chi-Min;Lee, Chil-Woo
    • The Journal of the Korea Contents Association
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    • v.10 no.8
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    • pp.11-17
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    • 2010
  • In this paper, we propose HMM-based upper-body gesture. First, to recognize gesture of space, division about pose that is composing gesture once should be put priority. In order to divide poses which using interface, we used two IR cameras established on front side and side. So we can divide and acquire in front side pose and side pose about one pose in each IR camera. We divided the acquired IR pose image using SVM's non-linear RBF kernel function. If we use RBF kernel, we can divide misclassification between non-linear classification poses. Like this, sequences of divided poses is recognized by gesture using HMM's state transition matrix. The recognized gesture can apply to existent application to do mapping to OS Value.

The Technique of Blocking Artifacts Reduction Method Based on Spatially Adaptive Image Restoration (공간 적응적 영상복원을 이용한 블록화 현상 제거 기법)

  • Kim, Tae-Keun;Woo, Hun-Bae;Paik, Joon-Ki
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.12
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    • pp.46-54
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    • 1998
  • In this paper we propose a fast adaptive image restoration filter using DCT-based block classification for reducing block artifacts in compressed images. In order to efficiently reduce block artifacts, edge direction of each block is classified by using the DCT coefficients, and the constrained least square (CLS) on the observation that the quantization operation in a series of coding process is a nonlinear and many-to-one mapping operator. And then we propose an approximated version of constrained optimization technique as a restoration process for removing the nonlinear and space-varying degradation operator. For real-time implementation, the proposed restoration filter can be realized in the form of a truncated FIR filter, which is suitable for postprocessing reconstructed images in HDTV, DVD, or video conference systems.

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Development of Suspended Sediment Concentration Measurement Technique Based on Hyperspectral Imagery with Optical Variability (분광 다양성을 고려한 초분광 영상 기반 부유사 농도 계측 기법 개발)

  • Kwon, Siyoon;Seo, Il Won
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.116-116
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    • 2021
  • 자연 하천에서의 부유사 농도 계측은 주로 재래식 채집방식을 활용한 직접계측 방식에 의존하여 비용과 시간이 많이 소요되며 점 계측 방식으로 고해상도의 시공간 자료를 측정하기엔 한계가 존재한다. 이러한 한계점을 극복하기 위해 최근 위성영상과 드론을 활용하여 촬영된 다분광 혹은 초분광 영상을 통해 고해상도의 부유사 농도 시공간분포를 측정하는 기법에 대한 연구가 활발히 진행되고 있다. 하지만, 다른 하천 물리량 계측에 비해 부유사 계측 연구는 하천에 따라 부유사가 비균질적으로 분포하여 원격탐사를 통해 정확하고 전역적인 농도 분포를 재현하기는 어려운 실정이다. 이러한 부유사의 비균질성은 부유사의 입도분포, 광물특성, 침강성 등이 하천에서 다양하게 분포하기 때문이며 이로 인해 부유사는 지역별로 다양한 분광특성을 가지게 된다. 따라서, 본 연구에서는 이러한 영향을 고려한 전역적인 부유사 농도 예측 모형을 개발하기 위해 실내 실험을 통해 부유사 특성별 고유 분광 라이브러리를 구축하고 실규모 수로에서 다양한 부유사 조건에 대한 초분광 스펙트럼과 부유사 농도를 측정하는 실험을 수행하였다. 실제 부유사 농도는 광학 기반 센서인 LISST-200X와 샘플링을 통한 실험실 분석을 통해 계측되었으며, 초분광 스펙트럼 자료는 초분광 카메라를 통해 촬영한 영상에서 부유사 계측 지점에 대한 픽셀의 스펙트럼을 추출하여 구축하였다. 이렇게 생성된 자료들의 분광 다양성을 주성분 분석(Principle Component Analysis; PCA)를 통해 분석하였으며, 부유사의 입도 분포, 부유사 종류, 수온 등과의 상관관계를 통해 분광 특성과 가장 상관관계가 높은 물리적 인자를 규명하였다. 더불어 구축된 자료를 바탕으로 기계학습 기반 주요 특징 선택 알고리즘인 재귀적 특징 제거법 (Recursive Feature Elimination)과 기계학습기반 회귀 모형인 Support Vector Regression을 결합하여 초분광 영상 기반 부유사 농도 예측 모형을 개발하였으며, 이 결과를 원격탐사 계측 연구에서 일반적으로 사용되어 오던 최적 밴드비 분석 (Optimal Band Ratio Analysis; OBRA) 방법으로 도출된 회귀식과 비교하였다. 그 결과, 기존의 OBRA 기반 방법은 비선형성을 증가시켜도 좁은 영역의 파장대만을 고려하는 한계점으로 인해 부유사의 다양한 분광 특성을 반영하지 못하였으며, 본 연구에서 제시한 기계학습 기반 예측 모형은 420 nm~1000 nm에 걸쳐 폭 넓은 파장대를 고려함과 동시에 높은 정확도를 산출하였다. 최종적으로 개발된 모형을 적용해 다양한 유사 조건에 대한 부유사 시공간 분포를 매핑한 결과, 시공간적으로 고해상도의 부유사 농도 분포를 산출하는 것으로 밝혀졌다.

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The Information Modeling Method based on Extended IFC for Alignment-based Objects of Railway Track (선형중심 객체 관리를 위한 확장된 IFC 기반 철도 궤도부 정보모델링 방안)

  • Kwon, Tae Ho;Park, Sang I.;Seo, Kyung-Wan;Lee, Sang-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.31 no.6
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    • pp.339-346
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    • 2018
  • An Industry Foundation Classes(IFC), which is a data schema developed focusing on architecture, is being expanded to civil engineering structures. However, it is difficult to create an information model based on extended IFC since the BIM software cannot provide support functions. To manage a railway track based on the extended IFC, this paper proposed a method to create an alignment-centered separated railway track model and convert it to an extended IFC-based information model. First, railway track elements have been classified into continuous and discontinuous structures. The continuous structures were created by an alignment-based software, and discontinuous structures were created as independent objects through linkage of the discretized alignment. Second, a classification system and extended IFC schema for railway track have been proposed. Finally, the semantic information was identified by using the property of classification code and user interface. The availability of the methods was verified by developing an extended IFC-based information model of the Osong railway site.

Neuronal Spike Train Decoding Methods for the Brain-Machine Interface Using Nonlinear Mapping (비선형매핑 기반 뇌-기계 인터페이스를 위한 신경신호 spike train 디코딩 방법)

  • Kim, Kyunn-Hwan;Kim, Sung-Shin;Kim, Sung-June
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.7
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    • pp.468-474
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    • 2005
  • Brain-machine interface (BMI) based on neuronal spike trains is regarded as one of the most promising means to restore basic body functions of severely paralyzed patients. The spike train decoding algorithm, which extracts underlying information of neuronal signals, is essential for the BMI. Previous studies report that a linear filter is effective for this purpose and there is no noteworthy gain from the use of nonlinear mapping algorithms, in spite of the fact that neuronal encoding process is obviously nonlinear. We designed several decoding algorithms based on the linear filter, and two nonlinear mapping algorithms using multilayer perceptron (MLP) and support vector machine regression (SVR), and show that the nonlinear algorithms are superior in general. The MLP often showed unsatisfactory performance especially when it is carelessly trained. The nonlinear SVR showed the highest performance. This may be due to the superiority of the SVR in training and generalization. The advantage of using nonlinear algorithms were more profound for the cases when there are false-positive/negative errors in spike trains.

A Study on Performance Analysis of Image Interpolation Filters for Field-based Warping and Morphing (필드 기반 워핑과 모핑을 위한 영상 보간 필터의 성능 분석에 관한 연구)

  • Lee Hyoung-Jin;Kwak No-Yoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.5 no.6
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    • pp.504-510
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    • 2004
  • The objective of this paper is to propose the image interpolation method with pseudomedian filter for Field warping and morphing, and to evaluate and analyze its subjective image quality. The Field warping relatively gives rise to more computing overhead, but it can use the control line to control the warping result with more elaboration. Due to the working characteristics of the image warping and morphing process, various complex geometrical transformations occur and a image interpolation technique is needed to effectively process them. Of the various interpolation techniques, bilinear interpolation which shows above average performance is the most widely used. However, this technology has its limits in the reconstructivity of diagonal edges. The proposed interpolation method is to efficiently combine the bilinear interpolation and the pseudomedian filter-based interpolation which shows good performance in the reconstructivity of diagonal edges. According to the proposed interpolation method, we could get more natural warping and morphing results than other interpolation methods.

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Design of an observer-based decentralized fuzzy controller for discrete-time interconnected fuzzy systems (얼굴영상과 예측한 열 적외선 텍스처의 융합에 의한 얼굴 인식)

  • Kong, Seong G.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.5
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    • pp.437-443
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    • 2015
  • This paper presents face recognition based on the fusion of visible image and thermal infrared (IR) texture estimated from the face image in the visible spectrum. The proposed face recognition scheme uses a multi- layer neural network to estimate thermal texture from visible imagery. In the training process, a set of visible and thermal IR image pairs are used to determine the parameters of the neural network to learn a complex mapping from a visible image to its thermal texture in the low-dimensional feature space. The trained neural network estimates the principal components of the thermal texture corresponding to the input visible image. Extensive experiments on face recognition were performed using two popular face recognition algorithms, Eigenfaces and Fisherfaces for NIST/Equinox database for benchmarking. The fusion of visible image and thermal IR texture demonstrated improved face recognition accuracies over conventional face recognition in terms of receiver operating characteristics (ROC) as well as first matching performances.