• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.136-138
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• 2022

Edge detection includes information such as the shape, position, size, and material of an object with respect to an image, and is a very important factor in analyzing the characteristics of the image. Existing edge detection methods include Sobel edge detection filter, Roberts edge detection filter, Prewitt edge detection filter, and LoG (Lapacian of Gaussian) using secondary differentials. However, these methods have a disadvantage in that the edge detection results are somewhat insufficient because a fixed weight mask is applied to the entire image area. Therefore, in this paper, we propose an edge detection algorithm that increases edge detection characteristics by considering the center pixel in the mask. In addition, in order to confirm the proposed edge detection performance, it was compared through simulation result images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2975-2980
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• 2015

Edge detection is one of image processing techniques applied for a variety of purposes in a number of areas and it is used as a necessary pretreatment process in most applications. Detect this edge has been conducted in various fields at domestic and international. In the conventional edge detection methods, there are Sobel, Prewitt, Roberts and LoG, etc using a fixed weights mask. Since conventional edge detection methods apply the images to the fixed weights mask, the edge detection characteristics appear somewhat insufficient. Therefore in this study, to complement this, preprocessing using gray-level transformation function and algorithm finding final edge using maximum and minimum value of estimated mask by local mask are proposed. And in order to assess the performance of proposed algorithm, it was compared with a conventional Sobel, Roberts, Prewitt and LoG edge detection methods.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.176-180
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• 1992

At the KACC'91 conference, we proposed a method of automatic detection of shape of the faulty holes of a shadow mask which is used in a cathode-ray tube of a color television. In this method, the image data are taken from two areas of the mask with CCD camera. Comparing the shape of holes in these two areas by use of a signal processing technique, we can find any fault in the shape of holes. This paper describes the effect of smoothing filters of effectively finding the faulty holes from the difference image data. A computer simulation and actual experiment with a shadow mask have shown that this method of fault detection is very effective for practical use.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.900-902
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• 2015

In the modern society, according to the advancement in digital image processing technology, edge detection is being utilized in various application sectors such as smart device and medical, etc. In existing edge detection methods, there are Sobel, Prewitt, Roberts and Laplacian, etc, which uses the mask. These previous methods are easy to implement but shows somewhat insufficient results. Therefore, in order to compensate the problems of existing methods, in this paper, an algorithm that detects the edge using the local mask and morphological operation was proposed and the detection performance was compared against the previous methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.210-216
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• 2014

The edge in the image is a part which the brightness changes rapidly between the object and the object or objects and background, and includes information of the features such as size, position, orientation, and texture of the object. The edge detection is the technique that acquires these information of the images, and now the researches to detect edges are making steady progress. Typical conventional edge detection methods are Sobel, Prewitt, Roberts using the first derivative operator and Laplacian method using the second derivative operator and so on. These methods is more or less insufficient that the characteristics of the edge detection in the image added salt and pepper noise. therefore, in this paper, an edge detection algorithm using modified mask that applies different size mask according to noise density of local mask is proposed.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.135-140
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• 2014

As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.

• 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 Institute of Information and Commucation Sciences Conference
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• 2013.10a
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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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• 2013.10a
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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.

• 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.