• Title/Summary/Keyword: Image Gradient

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An Automatic Extraction of Blood Flow Contour from Cardiac MRI (심장 MRI 영상에서 혈류 윤곽선의 자동 추출)

  • Lee, Hyeong-Jik;Jo, Sang-Hyeon;Choe, Heung-Mun
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.37 no.5
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    • pp.56-62
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    • 2000
  • In this paper, an automatic extraction of the blood flow contour from cardiac MRI is proposed. By using the GVF snake which has wider capture range than the conventional snake, and by automatically generating the initial points along the outside of the contour of the zero GVF field in the edge image of the cardiac MRI, the blood flow contour can be automatically extracted, even when the contours have boundary concavities due to the papillary muscles, without any manual initialization of the experts. Experiments are conducted on the various real cardiac MRIs including noise and papillary muscles, and the proposed method is proved to be efficient in automatic extraction of the blood contours even if they have the boundary concavities.

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An Efficient BLU Inspection Using Noise-Tolerant Context-free Attention Operator (잡음에 강건한 주목 연산자를 이용한 효과적인 BLU 얼룩 검사)

  • Park, Chang-Jun;Choe, Heung-Mun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.6
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    • pp.640-647
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    • 2001
  • In this paper, a noise-tolerant generalized symmetry transform(NTGST) is proposed as an effective attention operator for the spot detection in BLU inspection, in which various spots with variable sizes, shapes, gray levels, and low contrast, should be detected from the complex, noisy background with lattice shaped shading. The proposed NTGST takes into account the polarity of convergence and divergence of the radial orientation of the intensity gradient as well as it's magnitude and symmetry, and thereby can detect only the BLU spots from the noisy and lattice shaped shadows of background. Experiments are conducted on the BLU inspection image obtained by CCD camera, and the proposed NTGST is Proved to be effectively used in BLU inspection.

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Image Interpolation using directional edge weight (방향성 에지 윤곽선 가중치를 이용한 영상 보간)

  • Lee, Ou-Seb;Kim, Hyeong-Kyo
    • Journal of the Institute of Convergence Signal Processing
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    • v.11 no.1
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    • pp.26-31
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    • 2010
  • We proposed a new directional edge based interpolation, DEBI, by combining two weighted directional information to reduce blurred edges and annoying artifacts. Four isotropic gradient masks are employed in defining edge directions and they are proven to hold a first order derivative relation with respect to a rotating coordinate. Two minimum gradients among four absolute directional results are shown to be sufficient to describe slant edges efficiently. Compared with widely used bilinear and bicubic interpolation methods, the proposed algorithm results in a noticeable improvement along edge area.

In Vivo Three-dimensional Motion Analysis of the Shoulder Joint During Internal and External Rotation at 90 Degrees of Abduction, using wide Gantry MRI.

  • Koishi, Hayato;Goto, Akira;Yoshikawa, Hideki;Sugamoto, Kazuomi
    • The Academic Congress of Korean Shoulder and Elbow Society
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    • 2009.03a
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    • pp.175-175
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    • 2009
  • Despite its importance for the understanding of joint kinematics in vivo, there has been few studies about shoulder joints. The purpose of this study is to analyze the glenohumeral joint during internal and external rotation at 90 degrees of abduction using in vivo noninvasive motion analysis system. MRI was performed for the following seven positions from maximum internal rotation to maximum external rotation at intervals of 30 degrees. We used 3D-gradient echo sequencing (TR: 12 ms, TE: 5.8 ms, 0.8 mm-slice thickness). Our method is based on matching three-dimensional MR images by the similarity of the image intensity. We analyzed the in vivo three-dimensional motions of the glenohumeral and scapulothoracic joint during this motion. In scapla plane, the mean rotation angle of the glenohumeral join was 105.5 degrees ($SD{\pm}39.0^{\circ}$). The mean rotation angle of the scapulothracic joint was 27.5 degrees ($SD\;{\pm}\;7.7^{\circ}$). The contribution ratio is almost 3.8:1 of glenohumeral and scapulothracic joint respectively.

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Identification of boundary migration during the wound healing through the visualization of cell migrations (세포 운동 가시화를 통한 상처 치유 과정 내 경계 이동의 규명)

  • Jeong, Hyuntae;Lee, Jaesung;Shin, Jennifer Hyunjong
    • Journal of the Korean Society of Visualization
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    • v.18 no.2
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    • pp.10-17
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    • 2020
  • The curvature of wound boundaries has been identified as a key modulator that determines a type of force responsible for cell migration. While several studies report how certain curvatures of the boundary correlate with the rate at which the wound closes, it remains unclear how these curvatures are spatiotemporally formed to regulate the healing process. We investigated the dynamic changes in the boundary curvatures by visualizing cell migration patterns. Locally, cells at the convex boundary continuously move forward with transmitting kinetic responses behind to the cells away from the boundary, and cells at the concave boundary exhibit dramatic contracting motion, like a purse-string, when they accumulate enough negative curvatures to gain the thrust toward the void. Globally, the dynamics of boundary geometries are controlled by the diffusive flow of cells driven by the density gradient between the wound area and the cell layer.

COMPARISON OF DIFFERENT NUMERICAL SCHEMES FOR THE CAHN-HILLIARD EQUATION

  • Lee, Seunggyu;Lee, Chaeyoung;Lee, Hyun Geun;Kim, Junseok
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.17 no.3
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    • pp.197-207
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    • 2013
  • The Cahn-Hilliard equation was proposed as a phenomenological model for describing the process of phase separation of a binary alloy. The equation has been applied to many physical applications such as amorphological instability caused by elastic non-equilibrium, image inpainting, two- and three-phase fluid flow, phase separation, flow visualization and the formation of the quantum dots. To solve the Cahn-Hillard equation, many numerical methods have been proposed such as the explicit Euler's, the implicit Euler's, the Crank-Nicolson, the semi-implicit Euler's, the linearly stabilized splitting and the non-linearly stabilized splitting schemes. In this paper, we investigate each scheme in finite-difference schemes by comparing their performances, especially stability and efficiency. Except the explicit Euler's method, we use the fast solver which is called a multigrid method. Our numerical investigation shows that the linearly stabilized stabilized splitting scheme is not unconditionally gradient stable in time unlike the known result. And the Crank-Nicolson scheme is accurate but unstable in time, whereas the non-linearly stabilized splitting scheme has advantage over other schemes on the time step restriction.

Integrated Method for Text Detection in Natural Scene Images

  • Zheng, Yang;Liu, Jie;Liu, Heping;Li, Qing;Li, Gen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.11
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    • pp.5583-5604
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    • 2016
  • In this paper, we present a novel image operator to extract textual information in natural scene images. First, a powerful refiner called the Stroke Color Extension, which extends the widely used Stroke Width Transform by incorporating color information of strokes, is proposed to achieve significantly enhanced performance on intra-character connection and non-character removal. Second, a character classifier is trained by using gradient features. The classifier not only eliminates non-character components but also remains a large number of characters. Third, an effective extractor called the Character Color Transform combines color information of characters and geometry features. It is used to extract potential characters which are not correctly extracted in previous steps. Fourth, a Convolutional Neural Network model is used to verify text candidates, improving the performance of text detection. The proposed technique is tested on two public datasets, i.e., ICDAR2011 dataset and ICDAR2013 dataset. The experimental results show that our approach achieves state-of-the-art performance.

A convergence analysis of a differential method for 2-D motion parameter estimation (미분 추정 기법에 의한 2파원 이동 파라미터 추정의 수렴 특성 분석)

  • 이상희;유국열;김재균
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.23 no.7
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    • pp.1869-1882
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    • 1998
  • In this paper, we investigae convergence behaviors of a differential method for 2-D motion parameter estimation. While the differential method is widely studied for motion compensated prediction in video coding, little attention hs been paid to its convergence properties. Based on the nonseparable exponential covariance image model, we derive the estimates of update terms for the 2- and 6-parameter motion models. And, the effect of noise, spatial correlation, choice of spatial gradient measures, andthe size of a region, are quantitatively anlyzed in relation to the convergence speed. Some empirical results are presented to verify the analysis.

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A Study on the Morphological Analysis of Sperm Using Hough Transform (Hough변환을 이용한 정자의 형태학적 특성 분석방법에 관한 연구)

  • Park, Kwang-Suk;Yi, Won-Jin;Paick, Jae-Seung
    • Journal of Biomedical Engineering Research
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    • v.17 no.1
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    • pp.25-32
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    • 1996
  • A new analytic method has been developed for the analysis of sperm morphology using Hough transform. This method is based on the characteristic that sperm heads have elliptic shape in addition to the density difference with the background Sperm heads are represented in elliptic form with five parameter, and the optimal parameters are estimated by iterative Hough transform. To reduce processing time practically, we restricted the transformed space in minimum volume and moved the searching volume to the maximum gradient for the estimated error. Morphological parameters were calculated from estimated sperm head boundaries without further processing.

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Object Tracking with Sparse Representation based on HOG and LBP Features

  • Boragule, Abhijeet;Yeo, JungYeon;Lee, GueeSang
    • International Journal of Contents
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    • v.11 no.3
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    • pp.47-53
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    • 2015
  • Visual object tracking is a fundamental problem in the field of computer vision, as it needs a proper model to account for drastic appearance changes that are caused by shape, textural, and illumination variations. In this paper, we propose a feature-based visual-object-tracking method with a sparse representation. Generally, most appearance-based models use the gray-scale pixel values of the input image, but this might be insufficient for a description of the target object under a variety of conditions. To obtain the proper information regarding the target object, the following combination of features has been exploited as a corresponding representation: First, the features of the target templates are extracted by using the HOG (histogram of gradient) and LBPs (local binary patterns); secondly, a feature-based sparsity is attained by solving the minimization problems, whereby the target object is represented by the selection of the minimum reconstruction error. The strengths of both features are exploited to enhance the overall performance of the tracker; furthermore, the proposed method is integrated with the particle-filter framework and achieves a promising result in terms of challenging tracking videos.