• Title/Summary/Keyword: 적응적 에지 검출

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Detection of Pavement Borderline in Natural Scene using Radial Region Split for Visually Impaired Person (방사형 영역 분할법에 의한 자연영상에서의 보도 경계선 검출)

  • Weon, Sun-Hee;Kim, Gye-Young;Na, Hyeon-Suk
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.7
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    • pp.67-76
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    • 2012
  • This paper proposes an efficient method that helps a visually impaired person to detect a pavement borderline. A pedestrian is equipped with a camera so that the front view of a natural scene is captured. Our approach analyzes the captured image and detects the borderline of a pavement in a very robust manner. Our approach performs the task in two steps. In a first step, our approach detects a vanishing point and vanishing lines by applying an edge operator. The edge operator is designed to take a threshold value adaptively so that it can handle a dynamic environment robustly. The second step is to determine the borderlines of a pavement based on vanishing lines detected in the first step. It analyzes the vanishing lines to form VRays that confines the pavement only. The VRays segments out the pavement region in a radial manner. We compared our approach against Canny edge detector. Experimental results show that our approach detects borderlines of a pavement very accurately in various situations.

A Study on the Edge Detection using Adaptive Mask (적응 마스크를 이용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.10a
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    • pp.338-340
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    • 2012
  • In images, the edge is an important element to analyze characteristics of the image and has been used selectively at several applications. Even now, many researches to detect and take advantage of theses edges are underway and in initially to detect edges, methods using the relation of adjacent pixels are proposed. Characteristic of these methods is that the processing speed of the algorithms is fast, but the specific weighted values are applied to all the pixels regardless of the images equally. In recent years, the research of the edge detection algorithm to adapt according to the image has been actively underway, in order to complement the drawbacks of the existing methods. Therefore, in order to detect the edge excellent characteristics In this paper, we proposed algorithm using adaptive mask.

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A Study on the Edge Detection using Region Segmentation of the Mask (마스크의 영역 분할을 이용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.3
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    • pp.718-723
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    • 2013
  • In general, the boundary portion of the background and objects are the rapidly changing point and an important elements to analyze characteristics of image. Using these boundary parts, information about the position or shape of an object in the image are detected, and many studies have been continued in order to detect it. Existing methods are that implementation of algorithm is comparatively simple and its processing speed is fast, but edge detection characteristics is insufficient because weighted values are applied to all the pixels equally. Therefore, in this paper, we proposed an algorithm using region segmentation of the mask in order to adaptive edge detection according to image, and the results processed by proposed algorithm indicated superior edge detection characteristics in edge area.

An Efficient Intra-Field Deinterlacing Algorithm using Edges Extracted from the Interpolated Binary Image (보간된 이진 영상으로부터 검출된 정확한 에지를 이용한 효율적인 디인터레이싱 알고리즘)

  • Son, Joo-Yung;Lee, Sang-Hoon;Lee, Dong-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.5C
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    • pp.514-520
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    • 2009
  • This paper proposes a new deinterlacing algorithm which improves the performance of the spatial filter. Extracting exact edges is very important element of deinterlacing performance. So the proposed algorithm has interpolated locally adaptive-thresholded binary image, and extracted exact edges from the interpolated binary image. The values of pixels on edges extracted from binary image are interpolated using neighborhood lines on the same edge. With computer simulations for a variety of images, it is shown that the proposed algorithm is much better than traditional methods.

Adaptive morphological Wavelet-CNN Algorithm for the Color Image Edge detection (컬러 영상 에지 검출을 위한 적응 형태학적 WCNN 알고리즘)

  • Beak, Young-Hyun;Moon, Sung-Rung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.4
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    • pp.473-480
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    • 2004
  • This paper presents a new edge detection algorithm in color image. The proposed Adaptive morphological Wavelet-CNN algorithm is divided into two parts : The Adaptive morpholog and WCNN(Wavelet Cellular Neural Networks). It detects the optimal edge with applying this color image to WCNN algorithm, after it does level up a boundary side of a color image by using the adaptive morphology as the threshold of an input color image. Also, it is used not a conventional fixed mask edge detection method but variable mask method which is called a variable BBM. Finally, to show the feasibility of the proposed algorithm, this paper provides by simulation that the color image consists of 30.

Object Detection Algorithm in Sea Environment Based on Frequency Domain (주파수 도메인에 기반한 해양 물표 검출 알고리즘)

  • Park, Ki-Tae;Jeong, Jong-Myeon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.4
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    • pp.494-499
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    • 2012
  • In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

New edge detection algorithm and its application to a visual inspection (새로운 에지 검출 알고리듬과 시각적 검사에서의 그 응용)

  • Eun-Mi Kim;Cherl-Su Park
    • Journal of the Korea Computer Industry Society
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    • v.3 no.12
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    • pp.1725-1736
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    • 2002
  • We describe a characteristic behavior of edge signal intensity, the strictly monotonic variation of intensity across edges and propose a new algorithm for edge detection based on it. We define an extended directional derivatives, which is nonlocal and beyond scaling in the pixel space, to describe that the algorithm is adaptive to the various widths of edges and relevant as an optimal edge detection algorithm. As an industrial application of the algorithm, we discuss a simple computer vision procedure for an example of visual inspection.

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An adapt ive deinterlacing technique using edge information (Edge 정보를 이용한 적응적 deinterlacing 기법)

  • 나정은;이병욱;김인철
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.569-572
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    • 2001
  • 본 논문에서는 비월주사 방식의 영상을 순차주사 방식의 영상으로 변환하기 위한 deinterlacing 기법에 관하여 고찰한다. 먼저, 공간 영역 상에서 수행되는 기존의 deinterlacing 기법 중에서 우수한 성능을 보이는 것으로 알려진 ELA방법의 단점을 보완하기 위하여 적응적 ELA 알고리즘을 제안하였다. 기존의 ELA방법은 수평 edge를 검출할 수 없어 수평 edge 성분을 포함하는 화소 값은 원치 않는 값으로 보간 되는 결과를 가져왔다. 이를 개선시키기 위해 수평 edge를 효과적으로 검출하는 방법을 제안하고, 수평 에지 부분을 적절히 보간할 수 있는 적응적인 필터를 제안한다. 그 결과 수평 edge 부분에서의 개선으로 기존의 ELA 방법보다 더 나은 성능을 얻었다.

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Development of Edge Detection System Based on Adaptive Directional Derivative (적응성 방향 미분에 의한 에지 검출기의 구현)

  • Kim, Eun-Mi
    • Convergence Security Journal
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    • v.6 no.3
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    • pp.29-35
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    • 2006
  • In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.

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Design of Zip Code Recognition System Using Cluster Neural Network (클러스터 신경망을 이용한 우편번호 인식 시스템의 설계)

  • 김종석;홍연찬
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.2
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    • pp.132-140
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    • 2001
  • 최근에는 대부분의 우편물 봉투가 창이나 색깔을 포함하고 있다. 본 논문에서는 창이 있는 봉투와 색깔이 있는 우편 봉투 영상에서 구조적 방법을 분석하여 수취인 주소 영역을 자동적으로 추출하는 시스템을 제안하였다. 제안된 방법은 이치화전 에지 검출을 이용하여 문자열 추출 후 검출된 블록에 대해 적응 이치화를 적용함으로써 이치화 후 우편 번호를 검출할 때보다 우편 봉투의 숫자 패턴이 밝기 및 주변 환경에 의한 영향을 적게 받는다는 점에서 더 효율적이다.

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