• Proceedings of the IEEK Conference
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• 2002.06d
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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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• v.50 no.5
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• pp.281-286
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• 2013

In this paper, we propose a noise estimation method using edge detection. It is a filter-based noise estimation method. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use a modified rational filter which is robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of images and has better results than those of conventional filter-based noise estimation methods.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.883-885
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• 1995

Edges are one of the most important features used in various computer vision applications. Most of the known edge detection techniques are categorized into three gropus: First two approaches are to find gray level changes using first-order or second-order differentiation. The third method uses intrinsic propoeties of edges such as the result shown during scale space filtering. In this paper, we study various kind of edge detection techniques. Two images (Lenna image and a certain image which is composed of step, ramp, roof, and other artificial edge patterns) are used to compare different edge detection techniques and to verify the advantages and disadvantage of each techniques.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2982-2988
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• 2014

The edge detection is a pre-processing of such as image segmentation, image recognition, etc, and many related studies are being conducted both in domestic and abroad. Representative edge detection methods are Sobel, Prewitt, Laplacian, Roberts and Canny edge detectors. Such existing methods are possible for superb detections of edges if edges are detected from videos without noises. However, for video degraded by the salt-and-pepper noise, the edge detection characteristic is shown to be insufficient due to the noise influence. Therefore, in this study, the area is separated as the top, down, left and right from the mask's center pixel first to acquire a superb edge detection characteristic from the video damaged by the salt-and-pepper noise. And the algorithm that detects the final edge by applying the directional mask on the assumed factor of mask that is obtained according to the result of determination for the noise status of representative pixel value of each area.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.279-286
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• 2000

The objective of this research is to detect the papaya fruits on tree in an orchard. The detection of papaya on natural background is difficult because colors of fruits and background such as leaves are similarly green. We cannot separate it from leaves by color information. Therefore, this research will use shape information instead. First, we detect an interested object by detecting its boundary using edge detection technique. However, the edge detection will detect every objects boundary in the image. Therefore, shape description technique will be used to describe which one is the interested object boundary. The good shape description should be invariant in scaling, rotating, and translating. The successful concept is to use Fourier series, which is called "Fourier Descriptors". Elliptic Fourier Descriptors can completely represent any shape, which is selected to describe the shape of papaya. From the edge detection image, it takes a long time to match every boundary directly. The pre-processing task will reduce non-papaya edge to speed up matching time. The deformable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.151-156
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• 2006

This paper presents an background edge generation based automatic algorithm for detection of moving objects under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally, aligning and reorganizing this images. We develop an efficient approach for robust panoramic background edge generation as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The proposed method can be successfully realized in various monitoring systems like intrusion detection as well as video surveillance.

• 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.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2120-2123
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• 2003

This paper presents the moving object detection and tracking algorithm using edge information base on human perceptual system The human visual system recognizes shapes and objects easily and rapidly. It's believed that perceptual organization plays on important role in human perception. It presents edge model(GCS) base on extracted feature by perceptual organization principal and extract edge information by definition of the edge model. Through such human perception system I have introduced the technique in which the computers would recognize the moving object from the edge information just like humans would recognize the moving object precisely.