• Title/Summary/Keyword: Sobel Edge Detection Method

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Fast Mask Operators for the edge Detection in Vision System (시각시스템의 Edge 검출용 고속 마스크 Operator)

  • 최태영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.11 no.4
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    • pp.280-286
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    • 1986
  • A newmethod of fast mask operators for edge detection is proposed, which is based on the matrix factorization. The output of each component in the multi-directional mask operator is obtained adding every image pixels in the mask area weighting by corresponding mask element. Therefore, it is same as the result of matrix-vector multiplication like one dimensional transform, i, e, , trasnform of an image vector surrounded by mask with a transform matrix consisted of all the elements of eack mask row by row. In this paper, for the Sobel and Prewitt operators, we find the transform matrices, add up the number of operations factoring these matrices and compare the performances of the proposed method and the standard method. As a result, the number of operations with the proposed method, for Sobel and prewitt operators, without any extra storage element, are reduced by 42.85% and 50% of the standard operations, respectively and in case of an image having 100x100 pixels, the proposed Sobel operator with 301 extra storage locations can be computed by 35.93% of the standard method.

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Proposed Pre-Processing Method for Improving Pothole Dataset Performance in Deep Learning Model and Verification by YOLO Model (딥러닝 모델에서 포트홀 데이터셋의 성능 향상을 위한 전처리 방법 제안과 YOLO 모델을 통한 검증)

  • Han-Jin Lee;Ji-Woong Yang;Ellen J. Hong
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.4
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    • pp.249-255
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    • 2022
  • Potholes are an important clue to the structural defects of asphalt pavement and cause many casualties and property damage. Therefore, accurate pothole detection is an important task in road surface maintenance. Many machine learning technologies are being introduced for pothole detection, and data preprocessing is required to increase the efficiency of deep learning models. In this paper, we propose a preprocessing method that emphasizes important textures and shapes in pothole datasets. The proposed preprocessing method uses intensity transformation to reduce unnecessary elements of the road and emphasize the texture and shape of the pothole. In addition, the feature of the porthole is detected using Superpixel and Sobel edge detection. Through performance comparison between the proposed preprocessing method and the existing preprocessing method, it is shown that the proposed preprocessing method is a more effective method than the existing method in detecting potholes.

Edge Detection Method using Modified Coefficient Masks (변형된 계수 마스크를 이용한 에지 검출 방법)

  • Lee, Chang-Young;Chung, Suk-Moon;Kim, Nam-Ho
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.218-223
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    • 2013
  • The performances of previous edge detection methods such as Sobel, Prewitt, and LoG(Laplacian of Gaussian) are insufficient for images degraded in AWGN(additive white Gaussian noise). Therefore, in this paper, we proposed an edge detection algorithm using a modified coefficient masks with gradient masks and distance weight mask. In order to confirm and verify the performance of the proposed algorithm, we simulated and compared proposed algorithm to conventional methods on various standard images added AWGN with a standard deviation ${\sigma}$=15, 30 and proposed algorithm shows superior edge detection characteristics in processed images.

Region Separateness-based Edge Detection Method (영역의 분할정도에 기반한 에지 검출 기법)

  • Seo, Suk-T.;Jeong, Hye-C.;Lee, In-K.;Kwon, Soon-H.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.7
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    • pp.939-944
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    • 2007
  • Edge is a significant element to represent boundary information between objects in images. There are various edge detection methods, which are based on differential operation, such as Sobel, Prewitt, Roberts, Canny, Laplacian, and etc. However the conventional methods have drawbacks as follow : (i) insensitivity to edges with gentle curve intensity, (ii) detection of double edges for edges with one pixel width. For the detection of edges, not only development of the effective operators but also that of appropriate thresholding methods are necessary. But it is very complicate problem to find an appropriate threshold. In this paper, we propose an edge detection method based on the region separateness between objects to overcome the drawbacks of the conventional methods, and a thresholding method for the proposed edge detection method. We show the effectiveness of the proposed method through experimental results obtained by applying the proposed and the conventional methods to well-known test images.

A Study on Edge Detection Algorithm using Grey Level Converting Function (그레이 레벨 변환 함수를 이용한 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Hwang, Yeong-Yeun;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.921-923
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    • 2015
  • Edge in the image includes the size, direction and location of objects. The existing detection methods for detecting this edge is a method using Sobel, Prewitt, Roberts and Laplacian, etc. These existing methods use a fixed weighted mask in order to detect the edge and have somewhat insufficient edge detection characteristics. Therefore in this paper, an algorithm that detects the edge by applying the grey level converting function according to the pixel distribution of local mask was proposed.

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Edge Detection by Compass Gradient Masks (컴패스 그라디언트 매스크에 의한 에지 검출)

  • 김영채;김명기
    • Proceedings of the Korean Institute of Communication Sciences Conference
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    • 1986.10a
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    • pp.53-55
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    • 1986
  • The edge detection system makes use or 3*3 compass gradient masks, which are well suited for digital implementation. Edge angles are quantized to eight equally spaced directions, suitable for chain coding of contours. Use of edge direction msp improves the simple thresholding of gradient modulus image. The concept of local connectivity of the edge direction map is useful improving the performance of this method as well as other edge operators such as Kirsch and Sobel.

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An Evaluation and Combination of Noise Reduction Filtering and Edge Detection Filtering for the Feature Element Selection in Stereo Matching (스테레오 정합 특징 요소 선택을 위한 잡음 감소 필터링과 에지 검출 필터링의 성능 평가와 결합)

  • Moon, Chang-Gi;Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.23 no.4
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    • pp.273-285
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    • 2007
  • Most stereo matching methods use intensity values in small image patches to measure the correspondence between two points. If the noisy pixels are used in computing the corresponding point, the matching performance becomes low. For this reason, the noise plays a critical role in determining the matching performance. In this paper, we propose a method for combining intensity and edge filters robust to the noise in order to improve the performance of stereo matching using high resolution satellite imagery. We used intensity filters such as Mean, Median, Midpoint and Gaussian filter and edge filters such as Gradient, Roberts, Prewitt, Sobel and Laplacian filter. To evaluate the performance of intensity and edge filters, experiments were carried out on both synthetic images and satellite images with uniform or gaussian noise. Then each filter was ranked based on its performance. Among the intensity and edge filters, Median and Sobel filter showed best performance while Midpoint and Laplacian filter showed worst result. We used Ikonos satellite stereo imagery in the experiments and the matching method using Median and Sobel filter showed better matching results than other filter combinations.

A Study on Edge Detection Algorithm using Modified Mask of Weighting (변형된 가중치 마스크를 이용한 에지검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.3
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    • pp.735-741
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    • 2014
  • Edge in images appears when a great difference shows up in light and shade between pixels and includes data of the subject's size, location direction and etc. The edge is generally detected by the methods such as Sobel, Roberts, Laplacian, LoG(Laplacian of Gaussian) and etc. However, in AWGN(additive white Gaussian noise) added images, quality of the edge becomes slightly uncertain. Therefore, this paper proposed edge detection algorithm using modified mask of weighting to improve the quality of the existing methods. And in order to verify the performance efficiency of the proposed method, processed image and PFOM(Pratt's figure of merit) has been used as valuation standard for a comparison with the existing methods.

Research on Water Edge Extraction in Islands from GF-2 Remote Sensing Image Based on GA Method

  • Bian, Yan;Gong, Yusheng;Ma, Guopeng;Duan, Ting
    • Journal of Information Processing Systems
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    • v.17 no.5
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    • pp.947-959
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    • 2021
  • Aiming at the problem of low accuracy in the water boundary automatic extraction of islands from GF-2 remote sensing image with high resolution in three bands, new water edges automatic extraction method in island based on GF-2 remote sensing images, genetic algorithm (GA) method, is proposed in this paper. Firstly, the GA-OTSU threshold segmentation algorithm based on the combination of GA and the maximal inter-class variance method (OTSU) was used to segment the island in GF-2 remote sensing image after pre-processing. Then, the morphological closed operation was used to fill in the holes in the segmented binary image, and the boundary was extracted by the Sobel edge detection operator to obtain the water edge. The experimental results showed that the proposed method was better than the contrast methods in both the segmentation performance and the accuracy of water boundary extraction in island from GF-2 remote sensing images.

A Study on Edge Detection Algorithm in Salt & Pepper Noise Environments (Salt & Pepper 잡음 환경에서 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.8
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    • pp.1973-1980
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    • 2014
  • Edge detection for such as image, lane and object recognition is important image processing method. And some traditional method for this, there are Sobel, Prewitt, Roberts, Laplacian, LoG(Laplacian of Gaussian) and so on. Characteristics of these methods are insufficient in the salt & pepper noise added image. In order to improve such a problem of conventional methods, in this paper, we proposed an algorithm applying the weighted mask for detecting an edge by setting the local mask centered on the adjacent of the central pixel if central pixel of the mask is non-noise, it is intactly set by element of estimated mask, after calculating estimated mask if it is noise.