• 한국정밀공학회지
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• 제14권10호
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• pp.28-34
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• 1997

This paper describes an automatic measurement method for the in-line inspection of assembly tolerances of cathod ray electron guns. The method uses an optical microscope with a CCD camera as a probe. An automatic gap recognition algorthm with digital image processing and a new software autofocus algorithm based on using an optimal edge detector have been developed to improve the measuring accuracy. An inspection system has been proposed and practically implemented for in-line inspection to a real factory automation line. The inspection system consists of a gap inspection part and an eyelet. Total time consumed for inspecting all measuring items is about 10 seconds and the repeatability is below .+-. 5 .mu. m

• Journal of Astronomy and Space Sciences
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• 제10권1호
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• pp.86-93
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• 1993

다중선 비례계수관에서 균일한 개스증폭도를 얻기 위한 방법에 대해 실험하였다. 양극선에 전압을 공급하는 일반적인 연결 방법으로 검출기 양쪽 끝단의 edge effect 때문에 개스증폭도의 균일성이 좋지 않았다. 따라서 전압보상법을 사용하여 개스중폭도의 균일성을 $\pm$1.6%(rms 값) 이내로 보정하였다.

• 한국통신학회논문지
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• 제21권7호
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• pp.1677-1684
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• 1996

The theory of optimal stack filtering has been used in difference of estimates(DoE) approach to the detection of intensity edges in noisy image. 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 produces the estimated edge map. In this paper, the DoE approach is modified by imposing a symmetry condition of the data used to train the two stack filers. Under this condition, the stack filters obtained are duals of each other. Only one filter must therefore be trained;the other is simply its dual. They also produce statistially unbiased estimates. This new technique is called the symmetric Difference of Estimates (SDoE) approach.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2003년도 하계학술대회 논문집
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• pp.90-93
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• 2003

본 논문에서는 watershed segmentation을 이용해서 특정한 영역의 윤곽선정보를 바탕으로 영상을 추출하는 방법을 제안한다. 일반적인 영역추출방법에는 폐곡선을 이용한 영역추출방법, snake라 불리는 에너지 최소화를 이용한 active contour 방법 등 여러 가지가 있다. 특히 이러한 방법에는 연산시간이 많이 걸린다는 단점이 있는데, 이러한 문제점을 해결하기 위해서 canny edge detector를 사용하여 윤곽선 정보를 추출하고, watershed segmentation으로 영상을 분할한 후 윤곽선 정보를 이용해서 특정 영상의 영역에 대한 부분을 병합하여 추출하는 방법을 사용하였다. 제안하는 방법으로 기존의 추출 방법중의 하나인 levelset과 비교 실험한 결과 거의 동일한 영상의 결과를 얻을 수 있었으며 연산시간을 줄일 수 있었다.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2003년도 춘계학술발표대회논문집
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• pp.431-434
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• 2003

In this paper, we propose an efficient method not only f3r producing accurate region segmentation, solving the over-segmentation problem of watershed algorithm but also f3r reducing post-processing time by reducing computation loads. Through this proposed method, region segmentation of neighboring objects and discrimination of similar intensities were effectively obtained. Input image of watershed algorithm has used the derivative-based detectors such as Sobel and Canny. But proposed method uses the pixels-similarity-based detector, that is, SUSAN. By adopting this proposed method, we can reduce the noise problem and solve the problem of over-segmentation and not lose the edge information of objects. We also propose Zero-Crossing SUSAN. With Zero-Crossing SUSAN, the edge localization, times and computation loads can be improved over those obtained from existing SUSAN

• 한국멀티미디어학회논문지
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• 제11권12호
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• pp.1649-1657
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• 2008

In this paper, to overcome the failure of binarization for the characters suffered from low contrast and non-uniform illumination in license plate character recognition system, we improved the binarization method by combining local thresholding with global thresholding and edge detection. Firstly, apply the local thresholding method to locate the characters in the license plate image and then get the threshold value for the character based on edge detector. This method solves the problem of local low contrast and non-uniform illumination. Finally, back-propagation Neural Network is selected as a powerful tool to perform the recognition process. The results of the experiments i1lustrate that the proposed binarization method works well and the selected classifier saves the processing time. Besides, the character recognition system performed better recognition accuracy 95.7%, and the recognition speed is controlled within 0.3 seconds.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1427-1430
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• 1987

The feature points of an image play a very important role in understanding the image. Especially, when an image is composed of lines, vertices of the image offer informations about its property and structure. In this paper, a series of process for extracting feature points from actual IC image is described. This result can be used to acquire CIF ( Caltech Intermediate Form ) file.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.275-278
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• 1999

In this paper, Dual PFD(Phase Frequency Detector) with improved phase locking time is proposed. The proposed PFD consists of positive and negative edge triggered D flip-flop. In order to confirm the characteristics of proposed PFD, HSPICE simulations are performed using a 0.25${\mu}{\textrm}{m}$ CMOS process. As a result of simulations, the proposed PFD has a characteristic of fast phase locking time with dead zone free.

• 대한전자공학회논문지
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• 제25권9호
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• pp.1081-1090
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• 1988

A series of procedures using image processing techniques is presented for extracting layout information fast and automatically from chip images. CIF (caltech intermediate form) is chosen for representing such information. First, line-edges are extracted using a line-edge detector. Then, thinning and noise removal procedures follow. Subsequent procedures are vertex extraction and vertex grouping. Finally, CIF is extracted from the coordinates of the grouped vertices. In this paper, the final process is applied to only metal layer. In experiments, this processing scheme is shown to be very effective in extracting CIF.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.321-325
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• 2004

Retinopathy of Prematurity (ROP) is a common retinal neovascular disorder of premature infants. It can be characterized by inappropriate and disorganized vessel. This paper present a method for blood vessel detection on infant retinal images. The algorithm is designed to detect the retinal vessels. The proposed method applies a Lapalacian of Gaussian as a step-edge detector based on the second-order directional derivative to identify locations of the edge of vessels with zero crossings. The procedure allows parameters computation in a fixed number of operations independent of kernel size. This method is composed of four steps : grayscale conversion, edge detection based on LOG, noise removal by adaptive Wiener filter & median filter, and Otsu's global thresholding. The algorithm has been tested on twenty infant retinal images. In cooperation with the Digital Imaging Research Centre, Kingston University, London and Department of Opthalmology, Imperial College London who supplied all the images used in this project. The algorithm has done well to detect small thin vessels, which are of interest in clinical practice.