• Title/Summary/Keyword: Edge method

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Measurement of the Modulation Transfer Function of Infrared Imaging System by Modified Slant Edge Method

  • Li, Hang;Yan, Changxiang;Shao, Jianbing
    • Journal of the Optical Society of Korea
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    • v.20 no.3
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    • pp.381-388
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    • 2016
  • The performance of a staring infrared imaging system can be characterized based on estimating the modulation transfer function (MTF). The slant edge method is a widely used MTF estimation method, which can effectively solve the aliasing problem caused by the discrete undersampling of the infrared focal plane array. However, the traditional slant edge method has some limitations such as the low precision of the edge angle extraction and using the approximate function to fit the edge spread function (ESF), which affects the accuracy of the MTF estimation. In this paper, we propose a modified slant edge method, including an edge angle extraction method that can improve the precision of the edge angle extraction and an ESF fitting algorithm which is based on the transfer function model of the imaging system, to enhance the accuracy of the MTF estimation. This modified slant edge method presents higher estimation accuracy and better immunity to noise and edge angle than other traditional methods, which is demonstrated by the simulation and application experiments operated in our study.

Edge detection for noisy image (잡음 영상에서의 에지 검출)

  • Koo, Yun Mo;Kim, Young Ro
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.3
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    • pp.41-48
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    • 2012
  • In this paper, we propose a method of edge detection for noisy image. The proposed method uses a progressive filter for noise reduction and a Sobel operator for edge detection. The progressive filter combines a median filter and a modified rational filter. The proposed method for noise reduction adjusts rational filter direction according to an edge in the image which is obtained by median filtering. Our method effectively attenuates the noise while preserving the image details. Edge detection is performed by a Sobel operator. This operator can be implemented by integer operation and is therefore relatively fast. Our proposed method not only preserves edge, but also reduces noise in uniform region. Thus, edge detection is well performed. Our proposed method could improve results using further developed Sobel operator. Experimental results show that our proposed method has better edge detection with correct positions than those by existing median and rational filtering methods for noisy image.

A Method for Quantitative Performance Evaluation of Edge Detection Algorithms Depending on Chosen Parameters that Influence the Performance of Edge Detection (경계선 검출 성능에 영향을 주는 변수 변화에 따른 경계선 검출 알고리듬 성능의 정량적인 평가 방법)

  • 양희성;김유호;한정현;이은석;이준호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.6B
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    • pp.993-1001
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    • 2000
  • This research features a method that quantitatively evaluates the performance of edge detection algorithms. Contrary to conventional methods that evaluate the performance of edge detection as a function of the amount of noise added to he input image, the proposed method is capable of assessing the performance of edge detection algorithms based on chosen parameters that influence the performance of edge detection. We have proposed a quantitative measure, called average performance index, that compares the average performance of different edge detection algorithms. We have applied the method to the commonly used edge detectors, Sobel, LOG(Laplacian of Gaussian), and Canny edge detectors for noisy images that contain straight line edges and curved line edges. Two kinds of noises i.e, Gaussian and impulse noises, are used. Experimental results show that our method of quantitatively evaluating the performance of edge detection algorithms can facilitate the selection of the optimal dge detection algorithm for a given task.

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Combining an Edge-Based Method and a Direct Method for Robust 3D Object Tracking

  • Lomaliza, Jean-Pierre;Park, Hanhoon
    • Journal of Korea Multimedia Society
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    • v.24 no.2
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    • pp.167-177
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    • 2021
  • In the field of augmented reality, edge-based methods have been popularly used in tracking textureless 3D objects. However, edge-based methods are inherently vulnerable to cluttered backgrounds. Another way to track textureless or poorly-textured 3D objects is to directly align image intensity of 3D object between consecutive frames. Although the direct methods enable more reliable and stable tracking compared to using local features such as edges, they are more sensitive to occlusion and less accurate than the edge-based methods. Therefore, we propose a method that combines an edge-based method and a direct method to leverage the advantages from each approach. Experimental results show that the proposed method is much robust to both fast camera (or object) movements and occlusion while still working in real time at a frame rate of 18 Hz. The tracking success rate and tracking accuracy were improved by up to 84% and 1.4 pixels, respectively, compared to using the edge-based method or the direct method solely.

Precise Edge Detection Method Using Sigmoid Function in Blurry and Noisy Image for TFT-LCD 2D Critical Dimension Measurement

  • Lee, Seung Woo;Lee, Sin Yong;Pahk, Heui Jae
    • Current Optics and Photonics
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    • v.2 no.1
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    • pp.69-78
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    • 2018
  • This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

The Edge Enhanced Error Diffusion Using Local Characteristic Weights (국부적 특성 가중치를 이용한 에지 강조 오차 확산 방법)

  • 곽내정;윤태승;유성필;안재형
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.381-384
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    • 2003
  • Among digital halftoning methods, error diffusion is a procedure for generating high quality bilevel images from continuous-tone images but blurs the edge information in the bilevel images. To solve the problem, we propose the edge enhanced error diffusion using the edge information of the original images. The edge enchanted weights is computed by adding local characteristic weights and input pixels multiplied a constant. Also, we combined the edge enhanced method with the adaptive error diffusion using human spatial and frequency perception characteristic. The performance of the proposed method is compared with conventional method by measuring the edge correlation. The halftoned images applied the proposed method get more fine quality due to the enchanced edge and better quality in halftoned image. And the detailed edge is preserved in the halftoned images by the proposed method.

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The Edge Enhanced Error Diffusion Appling Edge Information Weights (에지 정보 가중치를 적용한 에지 강조 오차 확산 방법)

  • 곽내정;양운모;유창연;한재혁
    • The Journal of the Korea Contents Association
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    • v.3 no.3
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    • pp.11-18
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    • 2003
  • Error diffusion is a procedure for generating high quality bilevel images from continuous-tone images but blurs the edge information. To solve this problem, we propose the improved method appling edge enhanced weights based on local characteristic of the original images. We consider edge information as local characteristic. First, we produce edges by appling 3$\times$3 sobel operator to the original image. The edge is normalized from 0 to 1. Edge information weights are computed by using sinusoidal function and the normalized edge information. The edge enhanced weights are computed by using edge information weights multiplied input pixels. The proposed method is compared with conventional methods by measuring the edge correlation and quality of the recovered images from the halftoned images. The proposed method provides better quality than the conventional method due to the enhanced edge and represents efficiently the detail edge. Also, the proposed method is improved in edge representation than the conventional method.

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A method for ultrasound image edge enhancement by using Probabilistic edge map (초음파 진단영상 대조도 개선을 위한 확률 경계 맵을 이용한 연구)

  • Choi, Woo-hyuk;Park, Won-hwan;Park, Sungyun
    • The Journal of the Society of Korean Medicine Diagnostics
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    • v.20 no.1
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    • pp.37-44
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    • 2016
  • Ultrasonic imaging is the most widely modality among modern imaging device for medical diagnosis. Nevertheless, medical ultrasound images suffer from speckle noise and low contrast. In this paper, we propose probabilistic edge map for ultrasound image edge enhancement using automatic alien algorithm. The proposed method used applied speckle reduced ultrasound imaging for edge improvement using sequentially acquired ultrasound imaging. To evaluate the performance of method, the similarity between the reference and edge enhanced image was measured by quantity analysis. The experimental results show that the proposed method considerably improves the image quality with region edge enhancement.

Flow Prediction-Based Dynamic Clustering Method for Traffic Distribution in Edge Computing (엣지 컴퓨팅에서 트래픽 분산을 위한 흐름 예측 기반 동적 클러스터링 기법)

  • Lee, Chang Woo
    • Journal of Korea Multimedia Society
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    • v.25 no.8
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    • pp.1136-1140
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    • 2022
  • This paper is a method for efficient traffic prediction in mobile edge computing, where many studies have recently been conducted. For distributed processing in mobile edge computing, tasks offloading from each mobile edge must be processed within the limited computing power of the edge. As a result, in the mobile nodes, it is necessary to efficiently select the surrounding edge server in consideration of performance dynamically. This paper aims to suggest the efficient clustering method by selecting edges in a cloud environment and predicting mobile traffic. Then, our dynamic clustering method is to reduce offloading overload to the edge server when offloading required by mobile terminals affects the performance of the edge server compared with the existing offloading schemes.

Simple and Cost-Effective Method for Edge Bead Removal by Using a Taping Method

  • Park, Hyeoung Woo;Kim, H.J.;Roh, Ji Hyoung;Choi, Jong-Kyun;Cha, Kyoung-Rae
    • Journal of the Korean Physical Society
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    • v.73 no.10
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    • pp.1473-1478
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    • 2018
  • In this study, we have developed a simple and cost-effective method to prevent edge bead formation by covering the edge of a chip-level substrate with heat-resistant tape during patterning using SU-8. Edge beads are a fundamental problem in photoresists and are particularly notable in high-viscosity fluids and thick coatings. Edge beads can give rise to an air gap between the substrate and the patterning mask during UV exposure, which results in non-uniform patterns. Furthermore, the sample may break since the edge bead is in contact with the mask. In particular, the SU-8 coating thickness of the chip-level substrates used in MEMS or BioMEMS may not be properly controlled because of the presence of edge beads. The proposed method to solve the edge bead problem can be easily and economically utilized without the need for a special device or chemicals. This method is simple and prevents edge bead formation on the sample substrate. Despite the small loss in the taping area, the uniformity of the SU-8 coating is improved from 50.9% to 5.6%.