• Title/Summary/Keyword: edge processing

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Edge Detection of Variable Image by Adaptive Threshold (자동 임계치에 의한 다양한 영상의 에지 추출)

  • Baek, Soon-Hwa
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.11a
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    • pp.739-742
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    • 2002
  • 본 논문에서는 에지 추출을 위하여 다양한 영상에 탄력적으로 적용되는 자동 임계치에 의한 에지 추출 방법을 제안한다. 자동 임계치는 Prewitt 연산자를 이용하여 얻어진 영상을 사용하여 구한다. 에지 추출(Edge Detection)은 영상처리에 있어 데이터의 양을 크게 줄일 수 있는 장점과 함께 각종 영상처리의 전처리로 이용되어지고 있는데 정확한 에지 추출은 영상을 이해하고 분석하는데 있어서 대단히 중요한 요소로 영상처리의 다양한 분야와 결합하여 이용되어 지고 있다. 본 논문에서 제안한 자동 임계치 알고리즘에 의한 에지 추출은 영상의 세세한 부분의 에지를 탐색하는데 효과적임을 알 수가 있었다.

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Recursive Morphological Hybrid Median Filter (반복적 수리 형태학을 이용한 하이브리드 메디안 필터)

  • 정기룡
    • Journal of the Korean Institute of Navigation
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    • v.20 no.4
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    • pp.99-109
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    • 1996
  • Though median filter is used for removing noise and smoothing image. But, the result of it has distortion around edge. And then, this paper proposes new noise removing algorithm by recursive morphological processing. Basic operation is same each other, but there is some different processing method between recursive morphology and general morphology theory. This recursive morphological filter can be viewed as the weighted order static filter, and then it has a weighted SE(structuring element). Especially using this algorithm to remove the 10% gaussian noise, this paper confirmed that PSNR is improved about 0.642~1.5757 db reserving edge well better than the results of the traditional median filter.

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Improved Preprocessing of Fingerprint Recognition using Edge and Sweat Gland Restoration (에지와 땀샘 보정을 통한 지문영상 인식의 개선된 전처리)

  • Kim, Sung-Dae;Jung, Soon-Ho
    • Proceedings of the Korea Information Processing Society Conference
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    • 2004.05a
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    • pp.695-698
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    • 2004
  • 본 논문에서는 지문 입력기로부터 입력된 지문영상에 대한 전처리 과정에서 기존의 단계들인 모폴로지와 이진화 과정 대신에 새로운 에지(Edge) 보정과 땀샘(sweat gland) 보정 방법을 적용하여 여러 잡음들을 빠르면서 효율적으로 제거하는 방법을 제안하고 이에 대한 실험 결과에서 이 제안된 방법이 기존의 방법들보다 빠르고 선명한 세선화 결과를 획득하게 됨을 보여준다.

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Edge detection and noise removal algorithm (외곽선 검출 및 잡음 제거 알고리즘)

  • Moon, Woo-Hyeok;Jung, Si-Hun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.945-947
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    • 2021
  • Canny Edge Detection은 필터와 방향벡터를 이용한 대표적인 외곽선 추출 알고리즘으로서 대부분의 외곽선 추출 연구에서 이를 변형하여 사용한다. 그러나 본 논문에서는 외곽선 추출의 전처리 과정으로서 이미지에서의 잡음을 제거하는 알고리즘과 이를 바탕으로 외곽선을 더욱 효율적으로 추출할 수 있는 독창적인 알고리즘을 제시한다.

Mobility-Aware Edge Caching Algorithm with Dynamic Content Popularity (동적 인기도 콘텐츠를 활용한 이동성 인식 엣지 캐싱 알고리즘)

  • Lee, Tae-Yoon;Lee, SuKyoung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.135-137
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    • 2022
  • 이동성 기반의 기존 엣지 캐싱 연구에서는 인기도가 짧은 시간 급격하게 변화하는 SNM(Shot Noise Model) 콘텐츠를 반영하지 않았다. 동적 인기도 특성을 다루지 않는 경우, 잦은 캐시 미스가 발생하므로 SNM 콘텐츠를 고려하는 것은 중요하다. 이에 본 논문은 이동성을 고려한 기존 연구에 SNM 콘텐츠를 함께 고려하고, 시뮬레이션을 통해 기존 연구 대비 제안 알고리즘의 향상된 캐시 적중률을 확인한다.

Moving Object Contour Detection Using Spatio-Temporal Edge with a Fixed Camera (고정 카메라에서의 시공간적 경계 정보를 이용한 이동 객체 윤곽선 검출 방법)

  • Kwak, Jae-Ho;Kim, Whoi-Yul
    • Journal of Broadcast Engineering
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    • v.15 no.4
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    • pp.474-486
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    • 2010
  • In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

A method for underwater image analysis using bi-dimensional empirical mode decomposition technique

  • Liu, Bo;Lin, Yan
    • Ocean Systems Engineering
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    • v.2 no.2
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    • pp.137-145
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    • 2012
  • Recent developments in underwater image recognition methods have received large attention by the ocean engineering researchers. In this paper, an improved bi-dimensional empirical mode decomposition (BEMD) approach is employed to decompose the given underwater image into intrinsic mode functions (IMFs) and residual. We developed a joint algorithm based on BEMD and Canny operator to extract multi-pixel edge features at multiple scales in IMFs sub-images. So the multiple pixel edge extraction is an advantage of our approach; the other contribution of this method is the realization of the bi-dimensional sifting process, which is realized utilizing regional-based operators to detect local extreme points and constructing radial basis function for curve surface interpolation. The performance of the multi-pixel edge extraction algorithm for processing underwater image is demonstrated in the contrast experiment with both the proposed method and the phase congruency edge detection.

Image Enhancement of an Infrared Thermal Camera Using Edge Detection Methods (에지 검출 방법을 이용한 열화상 카메라의 영상 개선)

  • Jung, Min Chul
    • Journal of the Semiconductor & Display Technology
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    • v.15 no.3
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    • pp.51-56
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    • 2016
  • This paper proposes a new image enhancement method for an infrared thermal image. The proposed method uses both Laplacian and Prewitt edge detectors. Without a visible light, it uses an infrared image for the edge detection. The method subtracts contour images from the infrared thermal image. It results black contours of objects in the infrared thermal image. That makes the objects in the infrared thermal image distinguished clearly. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using various infrared thermal images. The results show that the proposed method is successful for image enhancement of an infrared thermal image.

Edge Preserving Smoothing in Infrared Image using Relativity of Guided Filter

  • Kim, Il-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.12
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    • pp.27-33
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    • 2018
  • In this paper, we propose an efficient edge preserving smoothing filter for Infrared image that can reduce noise while preserving edge information. Infrared images suffer from low signal-to-noise ratio, low edge detail information and low contrast. So, detail enhancement and noise reduction play crucial roles in infrared image processing. We first apply a guided image filter as a local analysis. After the filtering process, we optimization globally using relativity of guided image filter. Our method outperforms the previous methods in removing the noise while preserving edge information and detail enhancement.

EdgeCPS Technology Trend for Massive Autonomous Things (대규모 디바이스의 자율제어를 위한 EdgeCPS 기술 동향)

  • Chun, I.G.;Kang, S.J.;Na, G.J.
    • Electronics and Telecommunications Trends
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    • v.37 no.1
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    • pp.32-41
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    • 2022
  • With the development of computing technology, the convergence of ICT with existing traditional industries is being attempted. In particular, with the recent advent of 5G, connectivity with numerous AuT (autonomous Things) in the real world as well as simple mobile terminals has increased. As more devices are deployed in the real world, the need for technology for devices to learn and act autonomously to communicate with humans has begun to emerge. This article introduces "Device to the Edge," a new computing paradigm that enables various devices in smart spaces (e.g., factories, metaverse, shipyards, and city centers) to perform ultra-reliable, low-latency and high-speed processing regardless of the limitations of capability and performance. The proposed technology, referred to as EdgeCPS, can link devices to augmented virtual resources of edge servers to support complex artificial intelligence tasks and ultra-proximity services from low-specification/low-resource devices to high-performance devices.