• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1150-1159
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• 2006

This paper proposed a curve progress control function of the area base instead of the existing edge indication function, in order to detect the brain ventricle area by utilizing a geodesic active contour model. The proposed curve progress control function is very effective in detecting the brain ventricle area and this function is based on the average brightness of the brain ventricle area which appears brighter in MRI images. Compared numerically by using various measures, the proposed method in this paper can detect brain ventricle areas better than the existing method. By examining images of normal and diseased brain's images by brain tumor, we compared the several brain ventricle detection algorithms with proposed method visually and verified the effectiveness of the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.183-188
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• 2010

In this paper we propose a detection method of the medial axis of the continuous stripes on the LoG scale-space. Our method detects the medial axis of continuous stripes iteratively by varying the scale of LoG operator. Small-scale LoG operator detects two +/- pole pairs centered on the edge positions of stripe by the zero-crossing detection. The more increase the scale of LoG scale-space, the more close two poles to the medial axis of stripe. The medial axis of continuous stripe is the position where two poles is overlapped. The proposed method detected robustly the medial axis of continuous stripes stronger than the thinning methods used to binary image.

• 한국지형공간정보학회:학술대회논문집
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• 2002.11a
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• pp.133-140
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• 2002

This paper presents a method for line segment grouping used for detection of various building roofs. First, by using edge preserving filtering. noise is eliminated and then images are segmented by watershed algorithm, which preserves location of edge pixels. To extract line segments between control points from boundary of each region, we calculate curvature of each pixel on the boundary and then find the control points. Line linking is performed according to direction and length of line segments and finally the location of line segments is adjusted using gradient magnitudes of all pixels of the line segment. The algorithm has been applied to aerial imagery and the results show accurate building roof detection.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.577-580
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• 2017

중합 효소 연쇄 반응 (PCR) 젤 전기영동 이미지에서 DNA 지문을 분석하기 위한 새로운 레인 검출 및 추적 알고리즘이 제안하였다. 이전에 여러 연구 결과가 보고되었지만 갑작스런 배경 밝기 차이와 구부러진 레인이 있는 이미지에서 레인을 정확하게 추출하는 것은 여전히 어려움이 있다. 우리는 평균 레인 폭과 레인 주기를 계산하기 위한 에지 기반 알고리즘을 제안한다. 본 논문에서 제안한 방법은 k-means 클러스터링 알고리즘을 이용하여 상승 에지와 하강 에지를 정확하게 추출하는 부화소(sub-pixel) 알고리즘을 적용하여 레인 폭과 주기를 추정한다. 구부러진 레인을 처리하기 위해 젤 이미지를 정상영역과 비정상영역으로 분할하고, 각 분할 된 이미지의 레인 중심을 추적한다. 우리가 제안한 방법의 성능을 평가하기 위해 534 레인을 포함한 32 개의 젤 이미지가 사용되었다. 실험 결과는 우리의 방법이 전처리 과정 없이 배경 차이와 구부러진 레인을 갖는 이미지에 강인함을 보여 주었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1280-1286
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• 2001

In this Study, we try to suggest a system that recognize worker's regular motion more effectively First, based on frame difference that separates still background from movable object to video that make a film of worker's motion. The next, with edge detection, estimating the center of motion could recognize continuous motion. By action cognition system that design in this research films worker's action using fixed CCTV to supplement problem of action awareness system that is applied in existent industry spot, various mountings to get action information minimized. Also, shorten session that need in awareness enforcing action awareness through image subtraction and edge detection between frame to reduce time necessary to draw worker's body part special quality, expense designed inexpensive action cognition system as being efficient.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.382-383
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• 2016

Canny edge detection of the image is composed of four kinds of Gaussian filter, gradient calculation, Non-maximum suppression, and Hypothesis Thresholding. Feature is the ratio between the vehicle body, the windows, and the wheels obtained from the edge image. Features that make the proportion of these vehicles are different for each respective model. We have identified by application of this algorithm where only a small vehicle.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.92-98
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• 2019

In this paper, we propose a deep learning system based on morphological neural network(MNN). The deep learning layers are morphological operation layer, pooling layer, ReLU layer, and the fully connected layer. The operations used in morphological layer are erosion, dilation, and edge detection, etc. Unlike CNN, the number of hidden layers and kernels applied to each layer is limited in MNN. Because of the reduction of processing time and utility of VLSI chip design, it is possible to apply MNN to various mobile embedded systems. MNN performs the edge and shape detection operations with a limited number of kernels. Through experiments using database images, it is confirmed that MNN can be used as a deep learning system and its performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.127-132
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• 2011

In this paper, we propose a novel method of adult image classification by combining skin color regions and edges in an input image. The proposed method consists of four steps. In the first step, initial skin color regions are detected by logical AND operation of all skin color regions detected by the existing methods of skin color detection. In the second step, a skin color probability map is created by modeling the distribution of skin color in the initial regions. Then, a binary image is generated by using threshold value from the skin color probability map. In the third step, after using the binary image and edge information, we detect final skin color regions using a region growing method. In the final step, adult image classification is performed by support vector machine(SVM). To this end, a feature vector is extracted by combining the final skin color regions and neighboring edges of them. As experimental results, the proposed method improves performance of the adult image classification by 9.6%, compared to the existing method.

• 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 Korean Information Science Society Conference
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• 2003.10b
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• pp.628-630
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• 2003

본 연구는 손의 형상을 복잡한 배경환경에서 손 영역을 안정적으로 검출, 인식하여 윈도우 플레이어의 기능을 제어하는 시스템을 제안하였다. 손은 형상이 매우 복잡하기 때문에 2차원 형상의 불변량에 해당하는 에지의 방향성 히스토그램을 이용하여 인식을 행한다. 이 방법은 복잡한 배경에서 피부색을 지닌 손 영역이 정확히 추출되며 손 형상을 인식하는데 있어서 수행속도가 빠르고 조명변화에 덜 민감하기 때문에 실시간 손 형상 인식에 적합하다. 본 논문에서 제안한 방법을 윈도우 플레이어 제어에 적용한 결과 안정적으로 제어 할 수 있었다.