• Title/Summary/Keyword: Nearest Neighbor Interpolation

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Imputation of Medical Data Using Subspace Condition Order Degree Polynomials

  • Silachan, Klaokanlaya;Tantatsanawong, Panjai
    • Journal of Information Processing Systems
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    • v.10 no.3
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    • pp.395-411
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    • 2014
  • Temporal medical data is often collected during patient treatments that require personal analysis. Each observation recorded in the temporal medical data is associated with measurements and time treatments. A major problem in the analysis of temporal medical data are the missing values that are caused, for example, by patients dropping out of a study before completion. Therefore, the imputation of missing data is an important step during pre-processing and can provide useful information before the data is mined. For each patient and each variable, this imputation replaces the missing data with a value drawn from an estimated distribution of that variable. In this paper, we propose a new method, called Newton's finite divided difference polynomial interpolation with condition order degree, for dealing with missing values in temporal medical data related to obesity. We compared the new imputation method with three existing subspace estimation techniques, including the k-nearest neighbor, local least squares, and natural cubic spline approaches. The performance of each approach was then evaluated by using the normalized root mean square error and the statistically significant test results. The experimental results have demonstrated that the proposed method provides the best fit with the smallest error and is more accurate than the other methods.

Estimation of Rotational Center and Angle for Image Stabilization (영상 안정화를 위한 회전중심 및 각도 추정기법)

  • Seok, Ho-Dong;Yoo, Jun;Kim, Do-Jong
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.7
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    • pp.611-617
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    • 2004
  • This paper presents a simple method of rotational motion estimation and correction for roll axis stabilization of an image. The scheme first computes the rotation center by taking least squares of selected local velocity vectors, and the rotational angle is found from special subset of motion vectors. Roll motion correction is then performed by the nearest neighbor interpolation technique. To show the effectiveness of our approach, the synthetic and real images are evaluated, resulting in better performance than the previous ones.

The Rotational Motion Stabilization Using Simple Estimation of the Rotation Center and Angle

  • Seok, Ho-Dong;Kim, Do-Jong;Lyou, Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.231-236
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    • 2003
  • This paper presents a simple approach on the rotational motion estimation and correction for the roll stabilization of the sight system. The algorithm first computes the rotational center from the selected local velocity vectors of related pixels by least square methods. And then, rotational angle is found from the special subset of the motion vector. Finally, motion correction is performed by the nearest neighbor interpolation technique. In order to show the performance of the algorithm, the evaluation for the synthetic and real image was performed. The test results show good performance compared with previous approach.

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A Motion Compensation based Frame Rate Up Conversion Algorithm (움직임 추정을 활용한 영상의 시간 해상도 향상 기법)

  • Park, Ji Yeol;Kim, Kyumok;Park, Jinwon;Jung, Seung-Won
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.04a
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    • pp.947-949
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    • 2015
  • 본 논문은 기존의 시간적으로 이웃한 프레임 사이의 움직임을 추정 보상하여 새로운 프레임을 생성하는 프레임률 향상 기법 (frame rate up conversion)을 제안한다. 움직임 추정(Motion Estimation)을 통하여 계산된 움직임 벡터를 이용하여 프레임을 생성하며, 생성된 프레임에서 발생되는 구명 (hole)과 중첩 (overlap) 영역을 처리하는 기법을 제안한다. 특히 k-NN 보간법(k-nearest neighbor interpolation)[3]과 중간값을 적응적으로 활용하여 향상된 화질의 영상을 생성한다. 실험 결과를 통하여 제안하는 기술의 우수성을 입증하였다.

A Motion Compensation based Frame Rate Up Conversion Algorithm (움직임 추정을 활용한 영상의 시간 해상도 향상 기법)

  • Park, Ji Yeol;Kim, Kyumok;Park, Jinwon;Jung, Seung-Won
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.1520-1522
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    • 2015
  • 본 논문은 기존의 시간적으로 이웃한 프레임 사이의 움직임을 추정 보상하여 새로운 프레임을 생성하는 프레임률 향상 기법 (frame rate up conversion)을 제안한다. 움직임 추정(Motion Estimation)을 통하여 계산된 움직임 벡터를 이용하여 프레임을 생성하며, 생성된 프레임에서 발생되는 구멍 (hole)과 중첩 (overlap) 영역을 처리하는 기법을 제안한다. 특히 k-NN 보간법(k-nearest neighbor interpolation)[3]과 중간값을 적응적으로 활용하여 향상된 화질의 영상을 생성한다. 실험 결과를 통하여 제안하는 기술의 우수성을 입증하였다.

Enhanced Image Magnification Using Edge Information (에지정보를 이용한 개선된 영상확대기법)

  • Je, Sung-Kwan;Cho, Jae-Hyun;Cha, Eui-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.12
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    • pp.2343-2348
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    • 2006
  • Image magnification is among the basic image processing operations. The most commonly used technique for image magnification are based on interpolation method(such as nearest neighbor, bilinear and cubic interpolation). However, the magnified images produced by the techniques that often appear a variety of undesirable image artifacts such as 'blocking' and 'blurring' or too takes the processing time into the several processing for image magnification. In this paper, we propose image magnification method which uses input image's sub-band information such as edge information to enhance the image magnification method. We use the whole image and not use the one's neighborhood pixels to detect the edge information of the image that isn't occurred the blocking phenomenon. And then we emphasized edge information to remove the blurring phenomenon which incited of edge information. Our method, which improves the performance of the traditional image magnification methods in the processing time, is presented. Experiment results show that the proposed method solves the drawbacks of the image magnification such as blocking and blurring phenomenon, and has a higher PSNR and Correlation than the traditional methods.

Robust Object Tracking based on Kernelized Correlation Filter with multiple scale scheme (다중 스케일 커널화 상관 필터를 이용한 견실한 객체 추적)

  • Yoon, Jun Han;Kim, Jin Heon
    • Journal of IKEEE
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    • v.22 no.3
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    • pp.810-815
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    • 2018
  • The kernelized correlation filter algorithm yielded meaningful results in accuracy for object tracking. However, because of the use of a fixed size template, we could not cope with the scale change of the tracking object. In this paper, we propose a method to track objects by finding the best scale for each frame using correlation filtering response values in multi-scale using nearest neighbor interpolation and Gaussian normalization. The scale values of the next frame are updated using the optimal scale value of the previous frame and the optimal scale value of the next frame is found again. For the accuracy comparison, the validity of the proposed method is verified by using the VOT2014 data used in the existing kernelized correlation filter algorithm.

A Study of an Collarette Extraction in Iris Image (홍채 영상에서 자율신경환 추출에 관한 연구)

  • 강진영;김장형
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.754-757
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    • 2003
  • In Oriental medicine, the shape of collarette that formed with position in iris of patients often used by health diagnotcian to grasp health condition. In this paper, we present method that effectively extract collarette that exist in Iris image. After proposed method detert iris area using circular edge detector, derides boundary candidate point through radial line search and threshold value establishment. And boundary candidate line is treated to use nearest neighbor calculation at each boundary candidate point, finally extracts collarette through linear interpolation. As a result of experimenting about iris images, We Confirmed that can be used as assistant tool of diagnostic system that can presume state of ventriculus of human body.

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Deep Learning Based Gray Image Generation from 3D LiDAR Reflection Intensity (딥러닝 기반 3차원 라이다의 반사율 세기 신호를 이용한 흑백 영상 생성 기법)

  • Kim, Hyun-Koo;Yoo, Kook-Yeol;Park, Ju H.;Jung, Ho-Youl
    • IEMEK Journal of Embedded Systems and Applications
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    • v.14 no.1
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    • pp.1-9
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    • 2019
  • In this paper, we propose a method of generating a 2D gray image from LiDAR 3D reflection intensity. The proposed method uses the Fully Convolutional Network (FCN) to generate the gray image from 2D reflection intensity which is projected from LiDAR 3D intensity. Both encoder and decoder of FCN are configured with several convolution blocks in the symmetric fashion. Each convolution block consists of a convolution layer with $3{\times}3$ filter, batch normalization layer and activation function. The performance of the proposed method architecture is empirically evaluated by varying depths of convolution blocks. The well-known KITTI data set for various scenarios is used for training and performance evaluation. The simulation results show that the proposed method produces the improvements of 8.56 dB in peak signal-to-noise ratio and 0.33 in structural similarity index measure compared with conventional interpolation methods such as inverse distance weighted and nearest neighbor. The proposed method can be possibly used as an assistance tool in the night-time driving system for autonomous vehicles.

A Study on the Earthwork Volume Computation and Topographic Analysis using DTM Interpolations (DTM 보간기법별 토공량 산정과 지형분석에 관한 연구)

  • Park, Woon-Yong;Kim, Chun-Young;Lee, Hyun-Woo
    • Journal of Korean Society for Geospatial Information Science
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    • v.9 no.1 s.17
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    • pp.39-47
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    • 2001
  • DTM(Digital Terrain Model) can play a key rule in a great number of the fields of construction Engineering. One of the most important application fields is to determine volume in that the total construction expenses is usually calculated through this. It therefore is necessary to the study on improving the precise of the determination using DTM on account of saving time and cost. On this study, 1:5000 topographic maps issued by NGI in 15 districts involved in Pusan city was digitalized to generate DTM at first. After this step, not only was the determination of the volume as well as readjusted area and height done for the sake of estimating the changable topography caused by cut & fill volume in future but also provided the model to calculate it as results. In addition, comparison among the interpolations, such as Inverse Distance Method and Nearest Neighbor, was respectively done to look over the differences of the volume estimated from each interpolation and also to find the most suitable method. As a result, the former yielded the largest values of area and the volume while the latter gave the smallest ones. Moreover, the values estimated on this study were closely similar to ones obtained by the government of Pusan.

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