• 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.

• 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.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.328-330
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• 2015

Edge is a characteristic information that can easily obtain the size, direction and location of objects included in the image, and the edge detection is utilized as a preprocess processing in various image processing application sectors such as object detection and object recognition, etc. For the conventional edge detection methods, there are Sobel, Prewitt and Roberts. These existing edge detection methods are easy to implement but the edge detection characteristics are somewhat insufficient as fixed weighted mask is applied. Therefore, in order to compensate the problems of existing edge detection methods, in this paper, an edge detection algorithm was proposed after applying the weighted value according to the standard deviation and means within the local mask.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2779-2785
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• 2014

Edge Detection is a technique that obtains the particular information of the image using the brightness variation of pixel values and utilized for preprocessing in various image processing sectors. The conventional edge detection methods such as Sobel, Prewitt and Roberts are processed by applying the same weighted value to the entire pixels regardless of pixel distrbution and provides somewhat insufficient edge detection results. therefore, this paper has proposed an edge detection method considering the direction and magnitute of pixels by applying a modified directional mask.

• 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.

• 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 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.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.630-632
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• 2012

Contemporary society has evolved in the digital information age. Because of this, use of various digital images has been increased. To process these images, various digital image processing methods are used. Edge detection methods, one of those, are utilized to various areas of application such as object recognition, line detection. To detect edge, there are many methods such as Sobel, Prewitt, Laplacian. Because images which are dealt with existing methods are processed in same methods regardless the distribution of gray-level in image, edge detection property is insufficient. Therefore, In this study, to improve shortcomings of existing methods an algorithm using modified expansion mask is proposed.