• Title/Summary/Keyword: edge processing

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The Edge-Based Motion Vector Processing Based on Variable Weighted Vector Median Filter (에지 기반 가변 가중치 벡터 중앙값 필터를 이용한 움직임 벡터 처리)

  • Park, Ju-Hyun;Kim, Young-Chul;Hong, Sung-Hoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.11C
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    • pp.940-947
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    • 2010
  • Motion Compensated Frame Interpolation(MCFI) has been used to reduce motion jerkiness for dynamic scenes and motion blurriness for LCD-panel display as post processing for high quality display. However, MCFI that directly uses the motion information often suffers from annoying artifacts such as blockiness, ghost effects, and deformed structures. So in this paper, we propose a novel edge-based adaptively weighted vector median filter as post-processing. At first, the proposed method generates an edge direction map through a sobel mask and a weighted maximum frequent filter. And then, outlier MVs are removed by average of angle difference and replaced by a median MV of $3{\times}3$ window. Finally, weighted vector median filter adjusts the weighting values based on edge direction derived from spatial coherence between the edge direction continuity and motion vector. The results show that the performance of PSNR and SSIM are higher up to 0.5 ~ 1 dB and 0.4 ~ 0.8 %, respectively.

Switching Filter for Preserving Edge Components in Random Impulse Noise Environments (랜덤 임펄스 잡음 환경에서 에지 성분을 보존하기 위한 스위칭 필터)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.6
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    • pp.722-728
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    • 2020
  • Digital image processing has been applied in a wide range of fields due to the development of IoT technology and plays an important role in data processing. Various techniques have been proposed to remove such noise, but the conventional impulse noise canceling methods are insufficient to remove noise of edge components of an image, and have a disadvantage of being greatly affected by random impulse noise. Therefore, in this paper, we propose an algorithm that effectively removes edge component noise in random impulse noise environment. The proposed algorithm calculates the threshold value by determining the noise level and switches the filtering process by comparing the reference value with the input pixel value. The proposed algorithm shows good performance in the existing method, and the simulation results show that the noise is effectively removed from the edge of the image.

Noise Removal and Edge Detection of Image by Image Structure Understanding (화상 구조 파악에 의한 화상의 잡음 제거 및 경계선 추출)

  • Cho, Dong-Uk
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.7
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    • pp.1865-1872
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    • 1997
  • This paper proposes not only the thresholding problem which has been one of the major problems in the pre-existing edge detection method but also the removal of blurring effect occurred at the edge regions due to the smoothing process. The structure of a given image is assigned as one of the three predefined image structure classes by evaluating its toll membership value to each reference structure class:The structure of an image belongs to the structure class which has the least cost value with the image. Upon the structure class assigned, noise removal and edge extraction precesses are performed, e.g., the smoothing algorithm is applied to the image if its structure belongs to the pure noise region class; edge extraction while removing the noise is performed simultaneously if the edge structure class. The proposed method shows that preventing the blurring effect can be usually seen in the edge images and extracting the edges with no using thresholding value by the experiments.

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Welding Bead Segmentation Algorithm Using Edge Enhancement and Active Contour (에지 향상과 활성 윤곽선을 이용한 용접 비드 영역화 알고리즘)

  • Mlyahilu, John N.;Kim, Jong-Nam
    • Journal of the Institute of Convergence Signal Processing
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    • v.21 no.4
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    • pp.209-215
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    • 2020
  • In this paper, we propose an algorithm for segmenting weld bead images using edge enhancement and active contours. In the proposed method, high-frequency filtering and contrast improvement are performed for edge enhancement, and then, by applying the active contour method, only the weld bead region can be obtained. The proposed algorithm detects an edge through high-frequency filtering and reinforces the detected edge by using contrast enhancement. After the edge information is improved in this way, the weld bead area can be extracted by applying the active contour method. The proposed algorithm shows better performance than the existing methods for segmenting the weld bead in the image. For the objective reliability of the proposed algorithm, it was compared with the existing high pass filtering methods, and it was confirmed that the welding bead segmentation of the proposed method is excellent. The proposed method can be usefully used in evaluating the quality of the weld bead through an additional procedure for the segmented weld bead.

A study on Wavelet function for Improved Edge Detection Properties (개선된 에지검출 특성을 위한 웨이브렛 함수에 관한 연구)

  • Bae, Sang-Bum;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.197-200
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    • 2007
  • Edge representing the boundary between two regions with the large brightness difference in image includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge in according to duration time and the amplitude of brightness variation, and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

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Line-Edge Detection Using New 2-D Wavelet Function (새로운 2-D 웨이브렛 함수를 이용한 라인-에지 검출)

  • Bae Sang-Bum;Kim Nam-Ho
    • Journal of Korea Multimedia Society
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    • v.8 no.2
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    • pp.174-180
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    • 2005
  • Points of sharp variations in image are the most important components when we analyze the features of image. And they include a variety of information about image's shape and location etc. So a lot of researches for detecting edges have been continued. Edge detection operators which were used at the early stage of the research were to utilize relations among neighboring pixels. These methods detect edge at all boundaries, therefore they perform edge detection twice about curves below some width such as line-edge. In the meantime, wavelet transform which is presented as a new technique of signal processing field provides multiscale edge detection and is being applied widely in many fields that analyze edge-like characteristic. Therefore, in this paper we detected line-edge with new 2-D wavelet function which is independent of line's width.

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A Study of Edge Detection for Auto Focus of Infrared Camera

  • Park, Hee-Duk
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.1
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    • pp.25-32
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    • 2018
  • In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

A High Speed Road Lane Detection based on Optimal Extraction of ROI-LB (관심영역(ROI-LB)의 최적 추출에 의한 차선검출의 고속화)

  • Cheong, Cha-Keon
    • Journal of Broadcast Engineering
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    • v.14 no.2
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    • pp.253-264
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    • 2009
  • This paper presents an algorithm, aims at practical applications, for the high speed processing and performance enhancement of lane detection base on vision processing system. As a preprocessing for high speed lane detection, the vanishing line estimation and the optimal extraction of region of interest for lane boundary (ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled. Image feature information is extracted only in the ROI-LB. Road lane is extracted using a non-parametric model fitting and Hough transform within the ROI-LB. With simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since outliers of edge at each block can be removed with clustering of edge orientation for each block within the ROI-LB, the performance of lane detection can be greatly improved. The various real road experimental results are presented to evaluate the effectiveness of the proposed method.

Quantitative Analysis of Spatial Resolution for the Influence of the Focus Size and Digital Image Post-Processing on the Computed Radiography (CR(Computed Radiography)에서 초점 크기와 디지털영상후처리에 따른 공간분해능의 정량적 분석)

  • Seoung, Youl-Hun
    • Journal of Digital Convergence
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    • v.12 no.11
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    • pp.407-414
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    • 2014
  • The aim of the present study was to carry out quantitative analysis of spatial resolution for the influence of the focus size and digital image post-processing on the Computed Radiography (CR). The modulation transfer functions of an edge measuring method (MTF) was used for the evaluation of the spatial resolution. The focus size of X-ray tube was used the small focus (0.6 mm) and the large focus (1.2 mm). We evaluated the 50% and 10% of MTF for the enhancement of edge and contrast by using multi-scale image contrast amplification (MUSICA) in digital image post-processing. As a results, the edge enhancement than the contrast enhancement were significantly higher the spatial resolution of MTF 50% in all focus. Also the spatial resolution of the obtained images in a large focus were improved by digital image processing. In conclusion, the results of this study should serve as a basic data for obtain the high resolution clinical images, such as skeletal and chest images on the CR.

Edge Detection Verification and Principle analysis about Cellular Automata (셀룰라 오토마타의 원리 분석과 에지 추출 검증)

  • Nam, Tae-Hee
    • Journal of the Korea Computer Industry Society
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    • v.9 no.1
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    • pp.29-38
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    • 2008
  • This treatise analyzed theoretical principle of Cellular Automata systematically. Specially, Cellular Automata is hinting that can handle function of various form using transition rule. Cellular Automata can embody various and complicated principle with simple identifying marks that is "State", "Neighborhood", "Program Rules". Specially, have eminent cognitive faculty in image processing field. Examined closely that the ability excels flying important Edge Detection in image processing using this Cellular Automata in treatise that see therefore.

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