• The Journal of Korean Institute of Communications and Information Sciences
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• 제12권4호
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• pp.405-413
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• 1987

In this paper, we have discussed three-type median filters(SQUARE, CROSS, X-SHAPE) that preserving edge in an original image while reducing random noise was introduced for image enhancement and edge detection on radar image. Since radar image have a number of parts of curve, we compared results produced by edge detection operater proposed for improving the parts of curve with results of using the existing edge detection methods, such as Roberts, Sobel, Prewitt, Laplacian and Kirsch.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.215-218
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• 2002

The edges of an image hold much of the information in that image. The edges tell where objects are, their shape and size, and something about their texture. An edge is where the intensity of an image moves from a low value to a high value. We introduce the edge detection using the differential operator with Sobel operator and describe a nonparametric Wilcoxon test based on statistical hypothesis testing for the detection of edges. This paper proposes an efficient edge detection using Van der Waerden's statistic in original and noisy images. We use the threshold determined by specifying significance level a and an edge-height parameter. Comparison with our statistical test and Sobel operator shows that Van der Waerden method perform more effectively in both noisy and noise-free images.

• Journal of the Institute of Electronics and Information Engineers
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• 제52권4호
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• pp.207-212
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• 2015

We propose a noise estimation method using edge detection in moving pictures. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use Sobel and morphological closing operators which are robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of moving images and has better results than those of existing noise estimation methods. Also, proposed algorithm can be efficiently applied to image and video applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2013년도 추계학술대회
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• pp.770-772
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• 2013

Edges on the images are widely used in preprocessing in various areas including recognition and detection of the object. As generally known edge detection methods, there is a method using mask and these methods are Sobel, Prewitt, Roberts, Laplacian operator and etc. Implementation of these existing edge detection methods is simple. However, when processing the impulse noise added images, the properties of edge detection is not sufficient. Accordingly, in order to compensate for the weakness of existing edge detection methods and to detect strong edges on the images which were damaged by impulse noise, the edge detection algorithm using transformed mask was proposed in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2013년도 추계학술대회
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• pp.782-784
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• 2013

As digital image processing technologies are developing, edges are being utilized in various areas. In the existing edge detection methods, there are mask methods which utilize Sobel, Prewitt, Roberts, Laplacian operator etc. To realize these existing edge detection methods is simple. But, in case that AWGN(additive white Gaussian noise) added images are processed, edge detection characteristics are slightly insufficient. Therefore, the edge detection algorithm using the standard deviation of local mask was suggested in this paper to compensate for the drawbacks in the existing detection methods and the suggested algorithm in AWGN environments showed excellent edge detection characteristics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.100-103
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• 2014

Currently, edge detection is utilized in various areas. Edge detection is the preprocessing process for image processing in general, and this is a technology that is considered essential for image processing. According, research on this subject is carried out incessantly. Edge has important image related elements such as size, direction and location of the object of an image. Numerous methods were proposed for the detection. Among them, the representative methods are Sobel, Prewitt, Roberts, Laplacian. However, these existing methods are rather lacking when it comes to the edge detection characteristics in case of the image with mixed noise. Therefore, this study presented edge detection method that utilizes median and average values for the elements depending on the size and location of local mask.

• Journal of Astronomy and Space Sciences
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• 제33권4호
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• pp.313-318
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• 2016

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

• Proceedings of the KIEE Conference
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.113-114
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• 2007

본 논문에서는 SSE(Streaming Sigle instruction multiple data Extensions)명령어를 이용한 고속 Sobel edge detection 알고리즘을 제안한다. SSE를 지원하는 CPU는 128bit의 SSE 레지스터를 보유하고 있으며 이에 속한 데이터는 한 번에 병렬적으로 처리 될 수 있다. 실험은 Sobel 연산에 대하여 순차처리 코딩, 이미지 처리 라이브러리인 OpenCV, MIL 8.0, IPP 5.2를 이용한 코딩, shift 알고리즘을 사용한 SSE 코딩, 제안하는 방법을 이용한 SSE 프로그램 코팅에 대해 각각의 수행 시간을 측정하고 이를 비교하였다. 실험결과 제안하는 방법은 순차코팅에 비해 약 12배, OpenCV에 비해 13배, MIL에 비해 2배 정도 빨랐으며, IPP에 대해선 약간 빠른 성능 향상을 보였다. 또한 일반적인 shift를 이용한 방법보다 제안하는 방법은 대략 1.5배 정도의 성능 향상이 있었다. 이를 통해 제안하는 방법은 라이브러리를 구입하는 비용을 들이지 않으며 추가적 하드웨어의 구입 없이도 PC에서 빠른 Sobel 연산을 수행 할 수 있음을 보였다.

• Journal of the Korean Institute of Intelligent Systems
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• 제11권6호
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• pp.454-458
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• 2001

Based on a fuzzy system representation of gray scale images, we derive and edge detection algorithm whose convolution kernel is different from the known kernels such as those of Robert's Prewitt's or Sobel's gradient. Our fuzzy system representation is an exact representation of the bicubic spline function which represents the gray scale image approximately. Hence the fuzzy system is a continuous function and it provides a natural way to define the gradient and the Laplacian operator. We show that the gradient at grid points can be evaluated by taking the convolution of the image with a 3$\times$3 kernel. We also that our gradient coupled with the approximate value of the continuous function generates an edge detection method which creates edge images clearer than those by other methods. A few examples of applying our methods are included.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제16권7호
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• pp.1518-1523
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• 2012

Due to development of visual media in various industrial sectors, the importance of image processing is increasing. Among the various image processing areas, edge detection is utilized widely for various fields such as object recognition, object segmentation, the medical and other industries. Edge includes the critical factors of images like size, direction and location. Then conventional methods such as Sobel, Prewitt, Roberts and Laplacian are proposed to detect edge. However, edge detection property of these methods is declined when they are applied to the image which corrupted by AWGN(Additive White Gaussian Noise). Therefore, an algorithm using modified weighted filter is proposed in this paper and our method has excellent property on edge detection.