• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.449-452
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• 2003

This paper propose a extracting method of the region for image using segmentation and edge information. First propose algorithm extract information using canny edge detector and the image was divided by watershed segmentation. And it extract the mage with edge information by merging region. Finally we compare the proposed method with levelset method. In the result proposed method not only extract the image with accurate region but also reduce operation time.

• Journal of information and communication convergence engineering
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• v.12 no.3
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• pp.193-197
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• 2014

Edges are a robust feature for object detection. In this paper, we present an edge-based background modeling method for the detection of moving objects. The edges in the image frames were mapped using robust Canny edge detector. Two edge maps were created and combined to calculate the ultimate moving-edge map. By selecting all the edge pixels of the current frame above the defined threshold of the ultimate moving edges, a temporary background-edge map was created. If the frequencies of the temporary background edge pixels for several frames were above the threshold, then those edge pixels were treated as background edge pixels. We conducted a performance comparison with previous works. The existing edge-based moving-object detection algorithms pose some difficulty due to the changes in background motion, object shape, illumination variation, and noises. The result of the performance evaluation shows that the proposed algorithm can detect moving objects efficiently in real-world scenarios.

• Convergence Security Journal
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• v.6 no.3
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• pp.29-35
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• 2006

In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.932-934
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• 2003

In this paper, time, studied about method that can analyze iris change to using differential image of iris image that put interval and films and utilize as patient's health examination according to iris change. Time, Differential mage of iris image that put interval and films ran be used usefully to search early diagnosis of disease and unfolding process etc.. of disease by showing definitely change by tine. In the case of iris diagnostic system, iris outside area extracts iris area and uses Differential image of before filming image and image that film present to use canny edge detector as there is cay to extract iris area as do not help in diagnostic and change analyzed comparison.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1696-1705
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• 1996

The theory of stack filtering, which is a generalization of median filtering, is used to the detection of intensity edges in noisey images. The proposed approach, called the Difference of Estimates(DoE) approach, is a new formulation of a morphological scheme which has been very sensitive to impulse noise. In this approach, stack filters are applied to a noisy image to obtain local estimates of the dilated and eroded versions of the noise-free image. Thresholding the difference between these two estimates yields the binary edge map. We find that this approach yields results comparable to those obtained with the Canny operator for images with additive Gaussian noise, burt works much better when the noise is impulsive.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2259-2264
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• 2014

For edge detection methods, there are Sobel, Prewitt, Roberts and Canny edge detector, and these methods have insufficient detection characteristics in the image corrupted by the impulse noise. Therefore in this paper, in order to improve these disadvantages of the previous methods and to effectively detect the edge in the impulse noise environment, using the $5{\times}5$ mask, the noise factors within the $3{\times}3$ mask based on the central pixel is determined, and depending on its status, for noise-free it is processed as is, and if noise is found, by obtaining the estimated mask using the adjacent pixels of each factor, an algorithm that detects the edge is proposed.

• Journal of Magnetics
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• v.18 no.3
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• pp.311-316
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• 2013

Digital image processing has increasingly been implemented in nanostructural analysis and would be an ideal tool to characterize the morphology and position of self-assembled magnetic nanoparticles for high density recording. In this work, magnetic nanoparticles were synthesized by the modified polyol process using $Fe(acac)_3$ and $Pt(acac)_2$ as starting materials. Transmission electron microscope (TEM) images of as-synthesized products were inspected using an image processing procedure. Grayscale images ($800{\times}800$ pixels, 72 dot per inch) were converted to binary images by using Otsu's thresholding. Each particle was then detected by using the closing algorithm with disk structuring elements of 2 pixels, the Canny edge detection, and edge linking algorithm. Their centroid, diameter and area were subsequently evaluated. The degree of polydispersity of magnetic nanoparticles can then be compared using the size distribution from this image processing procedure.

• 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.

• Ocean Systems Engineering
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• v.2 no.2
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• pp.137-145
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• 2012

Recent developments in underwater image recognition methods have received large attention by the ocean engineering researchers. In this paper, an improved bi-dimensional empirical mode decomposition (BEMD) approach is employed to decompose the given underwater image into intrinsic mode functions (IMFs) and residual. We developed a joint algorithm based on BEMD and Canny operator to extract multi-pixel edge features at multiple scales in IMFs sub-images. So the multiple pixel edge extraction is an advantage of our approach; the other contribution of this method is the realization of the bi-dimensional sifting process, which is realized utilizing regional-based operators to detect local extreme points and constructing radial basis function for curve surface interpolation. The performance of the multi-pixel edge extraction algorithm for processing underwater image is demonstrated in the contrast experiment with both the proposed method and the phase congruency edge detection.

• Journal of Computing Science and Engineering
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• v.8 no.3
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• pp.149-156
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• 2014

Skeletonization is a morphological operation that transforms an original object into a subset, which is called a 'skeleton'. Skeletonization has been intensively studied for decades and is a challenging issue especially for special target objects. This paper proposes a novel approach to the skeletonization of text images based on stroke width detection. First, the preliminary skeleton is detected by using a Canny edge detector with a Tensor Voting framework. Second, the preliminary skeleton is smoothed, and junction points are connected by interpolation compensation. Experimental results show the validity of the proposed approach.