• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.294-296
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• 1996

The process of detecting edge in an image is an important component of many Pattern Recognition and Computer Vision applications. In many practical cases, there exist blurred images due to defocussing, movement of an object and so on. In addition, local perturbation noise can be added to the images. We propose the edge detection technique in blurred and noisy image. For this, we use Fuzzy pyramid linking mothod to remove noise and enhance the edge in images. We develop contrast intensifier using the concept of Fuzzy sets as a postprocessing.

• Journal of the Semiconductor & Display Technology
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• v.9 no.2
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• pp.79-85
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• 2010

In this paper, we propose a web inspection system (WIS) for real-time detection of paper defects which can cause critical fractures during papermaking process. Our system incorporates high speed line-scan camera, lighting system, and detection algorithm to provide robust and precise detection of paper defects in real-time. Since edge defects are very crucial to the paper fractures, our system focuses on the edge region of the paper instead of inspecting the whole paper area. In our algorithm, image projection and sub-pixel operation are utilized to detect the edge defects precisely and connected component labeling and shape analysis techniques are adopted to extract various kinds of the region defects. Experimental results revealed that our web inspection system is very efficient for detecting paper defects during papermaking processes.

• Transactions of Materials Processing
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• v.19 no.5
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• pp.320-324
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• 2010

Multi-Layer Ceramic Circuit(MLCC) in the face of thousands of fine pitch multi hole is processed. However, the fine pitch multi hole has a size of only a few micrometers. Therefore, in order to curtail the measurement time and reduce error, the image processing measurement method is required. So, we proposed an image processing measurement algorithm which is required to accurately measure the fine pitch multi hole. The proposed algorithm gets image of the fine pitch multi hole, extracts object from the image by morphological process, and extracts the parameters of its position and feature by edge detecting process. In addition, we have used the sub-pixel algorithm to improve accuracy. As a result, the proposed algorithm shows 97% test-retest measurement reliability within 2 ${\mu}m$. We found that the algorithm was wellsuited for measuring the fine pitch multi hole.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.83-90
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• 2011

In cell biology area, microscopy enables detecting objects inside cells that are stained or fluorescently tagged. It is disadvantageous for observing these objects because of the noisy characteristics of their environmental surrounding. In this paper, a framework is proposed to increase the throughput and reliability for analysis of these images. First, we apply adaptive beamlet transform to extract edges meaningfully followed by orientation, location, and length in different scales. Then, a post-process is implemented to extend and map them onto original image. Our proposed scheme is compared with Canny edge detector and conventional beamlet transform from four evaluation aspects. It produces better results when experiments are conducted on real images. Much better results for observing internal parts make this framework competitive for analysis of cell images.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.40 no.2
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• pp.37-42
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• 2008

Defects of corrugated board were limiting factors to the corrugated industry's growth. On-line detecting systems of defects are beneficial to increase profits of the corrugated board companies by reducing base paper consumption, increasing process reliability, and increasing productivity. By replacing naked eye inspection of defects to a defects detecting system, continuous inspection without fatigue may guarantee final products quality. The system was developed, which was consisted of line scan CCD camera, lens, illuminating parts, high speed image processor, software, various input parts, and output parts. First installation location of the system was at before fluting process after base paper unwinding, and surface of liner board was inspected by the system. Second installation location was after fluting process and combining process for liner board. Production loss includes ragged appearance of edge, irregular flute shape, wrong combination of flute, score cracking, defects in base paper, and flute cracking. The production loss was analyzed before and after the system installation at a commercial domestic mill. The production loss ratio was defined as a production loss weight per total production weight. The production loss ratio before the installation was decreased a lot from 1.28%(during 3 months before installation) to 0.76%(during 12 months after the first installation) and to 0.25%(during 6 months after the second installation).

• Journal of the Korean Society for Precision Engineering
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• v.7 no.3
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• pp.75-82
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• 1990

Automatic monitoring of the cutting conditions is one of the most improtant technologies in machining. In this study, the feasibility in applying acoustic emission(AE) signals for the in-process detection of endmill wear and fracture has been investigated by performing experimental test on the NC vertical milling machine with SM45C for specimen. As the results of detecting and analyzing AE signals on various cutting conditions, the followings have confirmed. (1) The RMS value of acoustic emission is related sensitively to the cutting velocity, but is not affected largely by feed rate. (2) The burst type AE signals of high level have been observed when removing chips distorderly and discontinuously. (3) When the RMS value grows up rapidly due to the increase of wear the endmill are generally broken or fractured, but when the endmills fracture at the conditions of smooth chip-flow or built-up-edge(BUE) occurred frequently, the rapid change of the RMS arenot found. And it is expected that this technigue will be quite useful for in-process sensing of tool wear and fracture.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.817-825
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• 1997

Images reconstructed with EM algorithm have been observed to have checkerboard effects and have large distortions near edges as iterations proceed. We suggest a aimple algorithm of applying line process to the EM and Bayesian EM to reduce the distortions near edges. We show by simulation that this algorithm improves the clarity of the reconstructed image and has good properties based on root mean square error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1100-1105
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• 2006

Severe distortions of colors in the obtained images have made it difficult for color codes to expand their applications. To reduce the effect of color distortions on reading colors, it will be more desirable to statistically process as many pixels in the individual color region as possible, than relying on some regularly sampled pixels. This process may require segmentation, which usually requires edge detection. However, edges in color codes can be disconnected due tovarious distortions such as zipper effect and reflection, to name a few, making segmentation incomplete. Edge linking is also a difficult process. In this paper, a more efficient approach to reducing the effect of color distortions on reading colors, one that excludes precise edge detection for segmentation, was obtained by employing the k-means clustering algorithm. And, in detecting color codes, the properties of both six safe colors and grays were utilized. Experiments were conducted on 144, 4M-pixel, outdoor images. The proposed method resulted in a color-code detection rate of 100% fur the test images, and an average color-reading accuracy of over 99% for the detected codes, while the highest accuracy that could be achieved with an approach employing Canny edge detection was 91.28%.

• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.46-53
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• 2013

An inspection of nuclear fuel rods should be performed at remoteness from risks of high level radioactivity, and accuracy is required. Currently, inspection of the nuclear fuel rods is operated to monitor the video that recording an original nuclear fuel rods at remoteness because of the risks of radioactivity. In this paper, it is an implementation of the system was carried out in the process according to the image processing inspection of the nuclear fuel rods. The nuclear fuel rods are configured to use a bundle of plurality, in the image processing technology to verify this, the edge detection method is useful. We suggest to DoG technique to add threshold for the nuclear fuel rod edge detections. This is the new technique that optimized DoG. It is to deal with DoG and threshold to dual process. In this way, after detecting an edge of the nuclear fuel rods, by running a nuclear fuel rod inspection algorithm to determine the status of nuclear fuel rods. We applied the system using the new algorithm, and confirmed an excellent characteristic. In this study, it is considered to be able to be carried out more easily and securely inspect of nuclear fuel rods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1867-1873
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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. 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, an algorithm for detecting the edge is proposed by applying the cross mask based on the center pixel and up, down, left and right mask based on the surrounding pixels of center pixel in order to solve these problems. And in order to assess the performance of proposed algorithm, it was compared with a conventional Sobel, Roberts, Prewitt and LoG edge detection methods.