• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1098-1100
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• 2019

영상 처리를 기반으로 하는 발굴 유물(고배) 도면 자동 생성 모델의 성능향상을 위한 투창 영역 자동 검출과 투창 영역의 영상 정보의 특성을 반영한 윤곽선 검출을 통한 고배 유물 도면화 성능 향상 모델을 제안하고 실험결과를 통해 투창 영역의 윤곽선 정확도가 향상되었음을 보인다. 투창 영역은 형태적 특성상 고배 유물의 도면 자동 생성 과정에서 왜곡된 윤곽선 검출의 가능성이 높은 부분이어서 투창 영역 윤곽선의 정확도를 높이는 것이 중요한 요소이다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.103-105
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• 2022

본 논문에서는 스네이크 알고리즘에서 복잡한 배경으로 인해 어긋난 윤곽선을 개선하는 방법을 제안한다. 스네이크 알고리즘은 능동 윤곽선 모델(active contour model)중 하나로, 사전 정의한 영역에서 시작하여 점진적으로 강한 변화가 감지되는 방향으로 윤곽선을 수정하는 방법이다. 그러나 이러한 방법은 강한 기울기 성분이 나타나는 배경에 취약하고, 대상의 불필요한 영역이 포함되거나, 필요한 영역이 포함되지 않는 문제가 발생한다. 제안하는 방법은 이미지에 원근 변환을 기반으로 한 스네이크 알고리즘을 반복적으로 적용하여 대상의 윤곽선을 온전히 추출한다. 이는 실험 데이터에서 평균 IoU가 약 11.5% 이상 증가한 것을 통해 올바른 윤곽선을 찾는데 효과적인 방법임을 알 수 있다.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.281-288
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• 2014

A method for edge detection using K-means clustering is proposed in this paper. The method is performed through there steps. Histogram equalizing is applied to the image for the uniformed intensity distribution. Pixels are clustered by K-means clustering technique. Then Sobel mask is applied to detect edges. Experiments showed that this method detected edges better than conventional method.

• Journal of Astronomy and Space Sciences
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• v.16 no.2
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• pp.255-264
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• 1999

We calculate the theoretical line profiles in order to investigate the influence of various velocity parameters. Line profiles are calculated by using the exponential velocoty law with two acceleration regions for orbital phases $\phi$ = 0.07 and $\phi$ = 0.06. From this compttation we find that the influence of the wind velocity gradient on a giant star is more important in the region near the star than in the region away from the star. The observed lines show stronger emission than the calculated line profiles and we interpret the difference is caused by the inhomogeniety in the atmosphere of 32 Cyg.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.79-87
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• 2005

This paper presents an active contour model for extracting accurate facial regions in complex environments. In the model, a contour is represented by a zero level set of level function φ, and evolved via level set partial differential equations. Then, unlike general active contours, skin color information that is represented by 2D Gaussian model is used for evolving and slopping a curve, which allows the proposed method to be robust to noise and varying pose. To assess the effectiveness of the proposed method it was tested with several natural scenes, and the results were compared with those of geodesic active contours. Experimental results demonstrate the superior performance of the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.664-666
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• 2002

기울기 연산자나 표면접합에 의한 윤곽추출과는 다른 본 논문에서는 확장과 수축방법론을 이용한 윤곽추출 및 잡음제거 방법론을 제안한다. 제안한 알고리즘은 전처리과정을 거친 후 확장과 수축 방법론을 적용함으로써 영상 윤곽 추출률을 높이고자한다 특히, 기존의 윤곽선 추출방법인 소벨과 프리위트알고리즘은 전처리과정인 미디안필터를 거친 후에 사용하였으며, 제안한 방법은 기존의 윤곽선 추출 필터를 거친 후에 사용하였다. 구체적으로 서술하면 확장알고리즘에서는 일정한 임계치를 초과하면 흰색으로 대치하였고, 수축 알고리즘에서는 검정색으로 대치했다. 기존의 잡음제거과정은 윤곽선의 손실은 없었으나 잡음제거가 소량 이루어졌으며, 제안한 방법에서는 약간의 윤곽선 손실을 보였으나 완전하게 잡음을 제거시킬 수 있었다.

• Journal of the Korea Computer Graphics Society
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• v.8 no.2
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• pp.1-7
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• 2002

The fast extraction of the silhouettes of a model is very useful for many applications in computer graphics and animation. In this paper, we present an efficient algorithm to compute a sequence of perspective silhouettes for a polyhedral model from a moving viewpoint. The viewpoint is assumed to move along a trajectory q(t), which is a space curve of a time parameter t. Then, we can compute the time-intervals for each edge of the model to be contained in the silhouette by two major computations: (i) intersecting q(t) with two planes and (ii) a number of dot products. If q(t) is a curve of degree n, then there are at most of n + 1 time-intervals for an edge to be in a silhouette. For each time point $t_i$ we can extract silhouette edges by searching the intervals containing $t_i$ among the computed intervals. For the efficient search, we propose two kinds of data structures for storing the intervals: an interval tree and an array. Our algorithm can be easily extended to compute the parallel silhouettes with minor modifications.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.731-741
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• 2000

This paper proposes a method to detect a facial region and extract facial features which is crucial for visual recognition of human faces. In this paper, we extract the MER(Minimum Enclosing Rectangle) of a face and facial components using projection analysis on both edge image and binary image. We use an active contour model(snakes) for extraction of the contours of eye, mouth, eyebrow, and face in order to reflect the individual differences of facial shapes and converge quickly. The determination of initial contour is very important for the performance of snakes. Particularly, we detect Minimum Enclosing Rectangle(MER) of facial components and then determine initial contours using general shape of facial components within the boundary of the obtained MER. We obtained experimental results to show that MER extraction of the eye, mouth, and face was performed successfully. But in the case of images with bright eyebrow, MER extraction of eyebrow was performed poorly. We obtained good contour extraction with the individual differences of facial shapes. Particularly, in the eye contour extraction, we combined edges by first order derivative operator and zero crossings by second order derivative operator in designing energy function of snakes, and we achieved good eye contours. For the face contour extraction, we used both edges and grey level intensity of pixels in designing of energy function. Good face contours were extracted as well.

• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.54-61
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• 2013

This paper presents a simplified hardware based edge detection circuit which is based on an analog correlator combining with the neighbor pixels in CMOS image sensor. A pixel element of the edge detector consists of an active pixel sensor and an analog correlator circuit which connects two neighbor pixels. The edge detector shares a comparator on each column that the comparator decides an edge of the target pixel with an adjustable reference voltage. The circuit detects image edge from CIS directly that reduces area and power consumption 4 times and 20%, respectively, compared with the previous works. And also it has advantage to regulate sensitivity of the edge detection because the threshold value is able to control externally. The fabricated chip has 34% of fill factor and 0.9 ${\mu}W$ of power per a pixel under 0.18 ${\mu}m$ CMOS technology.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.282-285
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• 2002

의료영상에서 윤곽선의 추출은 관심영역 대한 객관적인 수치 즉 면적, 부피, 장단축의 길이 등을 분석하고 3차원 재구성을 위해 선행되어야 하는 중요한 과정이다. 현재 윤곽선 추출에 대한 않은 방법들이 개발 중에 있으나 이 방법들은 한계를 지니고 있어 더 높은 수준의 처리가 요구된다. 본 논문에서는 active contour model(snake)을 이용하여 MR뇌 영상에서 종양을 추출하였다. Snake의 에너지 최적화 문제를 dynamic programming을 사용하여 개선하였으며 canny edge detection을 이용하여 잡음에 덜 민감하도록 하였다.