• Title/Summary/Keyword: 마스크 인식

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A Study on Edge Detection for Images Corrupted by AWGN using Modified Weighted Vector (AWGN에 훼손된 영상에서 변형된 가중치 벡터를 이용한 에지검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.7
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    • pp.1518-1523
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    • 2012
  • Due to development of visual media in various industrial sectors, the importance of image processing is increasing. Among the various image processing areas, edge detection is utilized widely for various fields such as object recognition, object segmentation, the medical and other industries. Edge includes the critical factors of images like size, direction and location. Then conventional methods such as Sobel, Prewitt, Roberts and Laplacian are proposed to detect edge. However, edge detection property of these methods is declined when they are applied to the image which corrupted by AWGN(Additive White Gaussian Noise). Therefore, an algorithm using modified weighted filter is proposed in this paper and our method has excellent property on edge detection.

Extracting Blood Vessels through Similarity Analysis and Intensity Correction (유사도 분석과 명암 보정을 통한 혈관 추출)

  • Jang Seok-Woo
    • Journal of Internet Computing and Services
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    • v.7 no.4
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    • pp.33-43
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    • 2006
  • This paper proposes a method to extract coronary arteries effectively in the angiography, In general. DSA(Digital Subtraction Angiography) is a well-established technique for the visualization of coronary arteries, DSA involves the subtraction of a mask image, an image of a heart before the injection of contrast medium, from a live image, However, this technique is sensitive to the movement of background and can cause wrong detection due to the variance of background intensity between two images. Therefore, this paper solves the structural problem resulted from background movement by selecting an image which has the least difference of movement through the similarity analysis of background texture, and it extracts only the blood vessels effectively through local intensity correction of the selected images, Experimental results show that the proposed method has the lower false-detection rate and higher accuracy rate than existing methods.

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Adaptive Segment-length Thresholding for Map Contour Extraction (등고선 추출을 위한 적응적 길이 임계화)

  • 박천주;오명관;전병민
    • The Journal of the Korea Contents Association
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    • v.3 no.4
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    • pp.23-28
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    • 2003
  • This paper describes, in order to extract contour from topographic map image, an adaptive segment-length thresholding using a threshold depended on target image. First of all, after recognizing the primary symbols and detecting two edges from the projection histogram of the elevation value area, the threshold value is determined by the distance between the edges. Then, the subdivision is peformed by searching a branch point and erasing its neighboring Hack pixels. And contour components are extracted by segment-length thresholding. The experimental result shows that the final image contains non-contour component of 2.41% and contour one of 97.59%.

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Navigational Path Detection Using Fuzzy Binarization and Hough Transform (퍼지 이진화와 허프 변환을 이용한 주행 경로 검출)

  • Woo, Young Woon
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.2
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    • pp.31-37
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    • 2014
  • In conventional methods for car navigational path detection using Hough transform, navigational path deviation of a car is decided in car navigational images with simple background. But in case of car navigational images having complex background with obstacles on the road, shadows, other cars, and so on, it is very difficult to detect navigational path because these obstacles obstruct correct detection of car navigational path. In this paper, I proposed an effective navigational path detection method having better performance than conventional navigational path detection methods using Hough transform only, and fuzzy binarization method and Canny mask are applied in the proposed method for the better performance. In order to evaluate the performance of the proposed method, I experimented with 20 car navigational images and verified the proposed method is more effective for detection of navigational path.

Photoluminescence analysis of patterned light emitting diode structure

  • Hong, Eun-Ju;Byeon, Gyeong-Jae;Park, Hyeong-Won;Lee, Heon
    • Proceedings of the Materials Research Society of Korea Conference
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    • 2009.05a
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    • pp.21.2-21.2
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    • 2009
  • 발광다이오드는 에너지 변환 효율이 높고 친환경적인 장점으로 인하여 차세대 조명용 광원으로 각광받고 있다. 하지만 현재 발광다이오드는 낮은 광추출효율로 인하여 미래의 수요를 충족시킬 수 있을 만큼 충분한 성능의 효율을 나타내지 못하고 있다. 발광다이오드의 낮은 광추출효율은 반도체소재와 외부 공기와의 큰 굴절률 차이로 인하여 발생하는 전반사 현상에 기인한 것으로 이 문제를 해결하기 위하여 발광다이오드 소자의 발광면 및 기판을 텍스처링하는 방법이 중요하게 인식되고 있다. 하지만 현재까지 패턴의 구조에 따른 광추출 특성을 분석한 연구는 미진한 상황이다. 본 연구에서는 임프린팅 및 건식식각 공정을 이용하여 다양한 구조의 나노 및 micron 급 패턴을 발광다이오드의 p-GaN층에 형성하였다. 발광다이오드 기판 위에 하드마스크로 사용하기 위한 SiO2를 50nm 증착한 후 그 위에 UV 임프린팅 공정을 진행하여 폴리머 패턴을 형성시켰다. 임프린팅 공정으로 형성된 폴리머 패턴을 CF4CHF3 플라즈마를 이용하여 SiO2를 건식식각하였고, 이후에 SiCl4와 Ar 플라즈마를 이용한 ICP 식각 공정을 진행하여 p-GaN층을 100nm 식각하였다. 마지막으로 BOE를 이용한 습식식각 공정으로 p-GaN층에 남아있는 SiO2층을 제거하여 p-GaN층에 sub-micron에서 micron급의 홀 패턴을 형성하였다. Photoluminescence(PL) 측정을 통해서 발광다이오드 소자에 형성된 패턴의 구조에 따른 광추출 특성을 분석하였다.

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Optical Implementation of Single Layer Neural Networks Using Diffraction Grating (회절격자를 이용한 광학적 단층 인식자의 구현)

  • 이재명;박성균;임종태;박한규
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.16 no.10
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    • pp.934-940
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    • 1991
  • A modified quantizing method is introduced to teach single layer learning algorithm, which is implemented optically. The proposed optical system consists of input masks, holographic diffraction grating. LCD and CCD camera. The 2 dimensional interconnections between input neurons and output neurons are realized using holographic phase grating, which is fabricated for equal intensity distribution of diffraction orders. The two gray levels of LCD act as binary weights for each interconnection. The weights are compensated according to the learning algorithm in which the amount of weights to be compensated is determined by comparing the output patterns with target patterns. The learning process is iterated until the predetermined conditions are satisfied. Optical experiments are performed for two learning rates, 0.5 and 0.9 and the experimental results show that the proposed system is useful for optical neural networks.

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Background segmentation of fingerprint image using RLC (RLC를 이용한 지문영상의 배경 분리)

  • 박정호;송종관;윤병우
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.4
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    • pp.866-872
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    • 2004
  • In fingerprint verification and identification, fingerprint and background region should be segmented. For this purpose, most systems obtain variance of brightness of X and Y direction using Sobel mask. To decide given local region is background or not, the variance is compared with a certain threshold. Although this method is simple, most fingerprint image does not separated with two region of fingerprint and background region. In this paper, we presented a new segmentation algorithm based on run-length connectivity analysis. For a given binary image after thresholding, suggested algorithm calculates RL of X and Y direction. Until the given image is segmented to two regions, small run region is successively inverted. Experimental result show that this algorithm effectively separates fingerprint region and background region.

The Extraction of the Singular Point from Ridge Direction Information for Fingerprint Recognition (지문인식 시 융선 방향정보로부터 특이점의 추출)

  • 이형교;윤동식;이종극
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.2
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    • pp.119-125
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    • 2004
  • The direction component uses mainly the sobel and FFT method. The sobel method is difficult to set representative direction when we wish to extract representative direction when we wish to extract representative direction component and the complicated processing process of sobel mask because same value appears in the low provision image or high provision image and we cannot accumulate tilt size in case of making accumulate after making unit vector to pixel. The method that uses FFT conversion for direction extraction is possible in case that ridge has correct direction specification and must use a special direction filter. After thinning the binary image to supplement above weak point in the paper, we extract direction component by pixel unit, and we extract the most direction components of pixel that exist in block of 8${\times}$8 pixels size as representative direction of ridge.

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A Study on Edge Detection using Grey-Level Morphology (그레이 레벨 모폴로지를 이용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.687-690
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    • 2017
  • Edge detection is an important step in determining the performance of lane recognition, object and pattern detection, and so on. And much research has been done until now. Sobel, Prewitt, Roberts, and Canny edge detection algorithms are widely known. However, these algorithms are often judged to be a non-edge region when processing a smooth change in brightness value. Therefore, in this paper, edge detection algorithm using gray-level morphology using erosion, expansion, open and close in the mask area. is proposed.

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Image Filter Using Fuzzy Logic (퍼지 논리를 이용한 영상 필터)

  • Jang, Dea-Sung;Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.05a
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    • pp.373-376
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    • 2009
  • 영상처리 기술은 인간의 시각에 기반을 둔 영상정보와 관련된 분야에서 중요한 기반 기술로써 현재 여러 분야에서 연구가 활발하게 진행 중이다. 여러 응용 분야에서 사용되는 영상처리의 세부 기술범위는 영상 변환, 영상 개선, 영상 복원, 영상 압축등과 같이 다양하며, 이런 영상처리 기술의 중요한 연구 목표 중의 하나는 정확한 정보 추출을 위한 영상정보의 개선에 있다. 영상정보의 개선은 영상의 해석과 인식을 위한 기본적인 과제이며, 영상에서 나타날 수 있는 잡음을 제거하는 영상처리 기술이 영상정보 개선의 한 분야라고 할 수 있다. 영상정보 개선을 위한 기존의 필터링 알고리즘은 잡음제거율이 높은 만큼 경계선의 보존이 어렵다는 단점이 있으며, 이를 보완하기 위해 다른 영상처리 알고리즘을 함께 응용하여 처리함으로써 처리시간이 증가되고 원 영상의 중요한 정보를 훼손할 가능성이 존재한다. 따라서 본 논문에서는 기존의 필터링 알고리즘의 문제점을 개선하는 동시에 잡음 제거율을 높일 수 있는 Fuzzy Mask Filter 알고리즘을 제안한다. Fuzzy Mask Filter 알고리즘은 마스크에서 얻은 정보를 Fuzzy Logic에 적용하여 임계값을 구하며, 구해진 임계값을 기준으로 출력영상의 화소값을 결정하는 알고리즘이다. 본 논문에서 제안한 알고리즘의 효율성을 검증하기 위해 Impulse 잡음과 Salt pepper 잡음을 임의로 생성하여 기존의 알고리즘과 비교한 결과, 제안된 방법이 잡음 영상에 존재하는 픽셀 정보를 훼손하지 않고 잡음을 효과적으로 제거한 것을 확인할 수 있었다.

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