• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1025-1028
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• 1999

After detecting the edge which is applying the morphological operators to the hybrid FCNN, we could analyze and compare. The hybrid FCNN is completely removed to the noise in the image, and worked in order to obtain the result image which is closest to the original image. Also, the morphological operator is applied to the image as the method in order to detect more good the edge than the conventional edge. FCNN which is the pipeline type is completely suitable to detecting the image processing as well as the hardware size. In this paper. we would make the structure elements of the morphological operator the variable template and the static template, and compare with the edge enhancement of two images. After being the result which is applying the variable template morphological operator and the static template morphological operator to the image, we could know that the edge images applying the variable template is superior in a edge enhancement side.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.801-803
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• 2014

In the modern society, image processing is utilized in various fields. Edge detection used for image processing as such is essential for most of the applications. Accordingly, there are studies conducted both in and out of Korea in order to detect edge. Representative edge detection methods include Sobel, Prewitt and Roberts. However, these methods are rather limited when it comes to the edge detection characteristics when used for the image with damaged AWGN(additive white Gaussian noise). Thus, this paper presented edge detection method utilizing local mask in order to overcome the shortcomings of the existing methods.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.2
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• pp.41-47
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• 2007

A fine segmentation algorithm is proposed for extracting objects in an image, which have both weak boundaries and highly non-convex shapes. The image has simple background colors or simple object colors. Two concepts, geometric attraction-driven flow (GADF) and edge-regions are combined to detect boundaries of objects in a sub-pixel resolution. The main strategy to segment the boundaries is to construct initial curves close to objects by using edge-regions and then to make a curve evolution in GADF. Since the initial curves are close to objects regardless of shapes, highly non-convex shapes are easily detected and dependence on initial curves in boundary-based segmentation algorithms is naturally removed. Weak boundaries are also detected because the orientation of GADF is obtained regardless of the strength of boundaries. For a fine segmentation, we additionally propose a local region competition algorithm to detect perceptible boundaries which are used for the extraction of objects without visual loss of detailed shapes. We have successfully accomplished the fine segmentation of objects from images taken in the studio and aphids from images of soybean leaves.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.53-62
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• 2001

In this paper, the hybrid function by local scale control is proposed to detect the optimal edges from blurred images. In the case of image capturing, some blurring is occurred by the characteristics of the illumination and the reflected light. During processing the blurred image, it is difficult to detect perfect edges. This algorithm proposed a new hybrid function which is merged Gaussian function and the second derivative of Gaussian function. And it detects the optimal edges applying directional edge detection by Canny algorithm as the scale factor of $\sigma$ in the given local mask has been changed after convolving the hybrid function for input image. In the result, the performance is confirmed that this algorithm is better than Sobel, Robert and Canny edge detector by analyzing the some test images. And the results is obtained 0.2 ㏈ ~ 14 ㏈ of PSNR than those conventional method.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.53-58
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• 2005

Points of sharp variations in images are the most important components when we analyze singularities of images. And they include a variety of information about the image's location and shape etc. So a lot of researches for detecting those edges have been continuing even now and at the early stage of the research, edge detection operators used relation among neighborhood pixels. However, such methods do not have excellent performance in the image which exists noise and can not detect edge selectively. In the meantime, the wavelet transform which is presented as a new technique of signal processing field is able to detect multiscale edge and is being applied widely in many fields that analyze singularities such as edge. For this reason, in this paper we detected image's line-edge elements with 2-D wavelet function, which is independent of line's width, in mixed noise environment.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.191-199
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• 2009

In this paper, the improved edge extract methods is proposed in order to extract edge. For the correct and fast detect, the binary image using the threshold value is applied for a experiment. For the experimental analysis, we compare the existing edge methods with the improved methods. Hereby, the exist methods are the sobel, robert, and prewitt. and the improved methods use the existing methods which is applied mask variations. The merits of the improved mothods have a result of a little erosion, a apparent edge. Specially, we use the grey image of medical image for the experimental analysis and then apply threshold value for a result image. After that, we acquire a apparent edge. For a quantitative analysis of the each methods, the each images was applied a histogram. As a result, we prove the merit of the improved methods using a analytical graph of the medical images.

• Journal of Korea Entertainment Industry Association
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• v.5 no.1
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• pp.127-133
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• 2011

Characters in natural image are an important information with various context. Previous work of character region detection algorithms is not detect of character region in case of image complexity and the surrounding lighting, similar background to character, so this paper propose an method of character region detection in natural image using edge and connected component by morphological reconstructions. Firstly, we detect edge using Canny-edge detector and connected component with local min/max value by morphological reconstructed-operation in gray-scale image, and labeling each of detected connected component elements. lastly, detected candidate of text regions was merged for generation for one candidate text region, Final text region detected by checking the similarity and adjacency of neighbor of text candidate individual character. As the results of experiments, proposed algorithm improved the correctness of character regions detection using edge and connected components.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.695-698
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• 2000

Round-cornering machines are mainly used for cornering of stiffners for ship buildings. In the present time they have been operated manually by operators. so they are need to be operated automatically without regard to any shapes of stiffners. We developed the automatic round cornering system which consists of CCd Camera, PC and laser diode to detect automatically the edge of stiffners to be processed

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.347-350
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• 2002

This paper describes eye detection algorithm using edge information and Support Vector Machine (SVM). We adopt an edge detection and labelling algorithm to detect isolated components. Detected candidate eye pairs finally verified by SVM using Radial Basis Function (RBF) kernel. A detection rate over the test set has been achieved more than 90%, and compared with template matching method. this proposed method significantly reduced FAR.