• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.161-164
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• 2003

This paper proposes a hierarchical approach to active shape model using wavelet transform. The proposed algorithm allows us to use both global shape characteristics and finer details for model deformation. The statistical properties of the wavelet transform of a deformable model are analyzed by principal component analysis and used as priors in the contour's deformation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06b
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• pp.51-56
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• 1999

본 논문에서는 동영상에서 의미 있는 객체 영역을 추출하기 위해, 사람이 첫 장에서 관심 있는 객체를 표시하고, 그 다음 프레임부터는 사람의 도움 없이 객체를 추적하는 반자동 (semi-automatic) 방식의 객체 추적 알고리즘에 대해 개선된 알고리즘을 제안하고 이를 구현하였다. 제안한 객체 추적 알고리즘은 이전 프레임의 객체의 움직임을 이용하여 현재 프레임에서 대략적인 객체의 위치를 찾은 후, 윤곽선의 불확실도를 조사하고, 윤곽선을 재조정하여 정확한 객체의 위치를 찾는다. 제안한 알고리즘은 다양한 영상에서 만족할 만한 결과를 얻었다.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.24.3-24
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• 2001

In cases where strong a priori knowledge about the object being analyzed is available, it can be embedded into the formulation of the snake model. When prior knowledge of shape is available for a specific application, information concerning the shape of the desired objects can be incorporated into the formulation of the snake model as an active contour model. In this paper we show Five points algorithm can be applied to design invariant energy.

• Journal of Information Processing Systems
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• v.5 no.1
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• pp.1-4
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• 2009

Level set methods are the numerical techniques for tracking interfaces and shapes. They have been successfully used in image segmentation. A new variational level set evolving algorithm without re-initialization is presented in this paper. It consists of an internal energy term that penalizes deviations of the level set function from a signed distance function, and an external energy term that drives the motion of the zero level set toward the desired image feature. This algorithm can be easily implemented using a simple finite difference scheme. Meanwhile, not only can the initial contour can be shown anywhere in the image, but the interior contours can also be automatically detected.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1972-1978
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• 2010

AAM(Active Appearance Model) is one of the most effective ways to detect deformable 2D objects and is a kind of mathematical optimization methods. The cost function is a convex function because it is a least-square function, but the search space is not convex space so it is not guaranteed that a local minimum is the optimal solution. That is, if the initial value does not depart from around the global minimum, it converges to a local minimum, so it is difficult to detect face contour correctly. In this study, an AAM-based face tracking algorithm is proposed, which is robust to various lighting conditions and backgrounds. Eye detection is performed using SIFT and Genetic algorithm, the information of eye are used for AAM's initial matching information. Through experiments, it is verified that the proposed AAM-based face tracking method is more robust with respect to pose and background of face than the conventional basic AAM-based face tracking method.

• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.433-444
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• 2000

The recognition of car plate was investigated by means of the enhanced fuzzy ART algorithm. The morphological information of horizontal and vertical edges was used to extract a plate area from a car image. In addition, the contour tracking algorithm by utilizing the SOFM was applied to extract the specific area which includes characters from an extracted plate area. The extracted characteristic area was recognized by using the enhanced fuzzy ART algorithm. In this study we propose the novel fuzzy ART algorithm different from the conventional fuzzy ART algorithm by the dynamical establishment of the vigilance threshold which shows a tolerance limit of unbalance between voluntary and saved patterns for clustering. The extraction rate obtained by using the morphological information of horizontal and vertical edges showed better results than that from the color information of RGB and HSI. Furthermore, the recognition rate of the enhanced fuzzy ART algorithm was improved much more than that of the conventional fuzzy ART and SOFM algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2429-2434
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• 2010

In this paper, we propose a method to extract and analyze palm line with fuzzy method. In order to extract the palm part, we transform the original RGB color space to YCbCr color space and extract sin colors ranging Y:65-255, Cb:25-255, Cr:130-255 and use it as a threshold. Possible noise is removed by 8-directional contour tracking algorithm and morphological characteristic of the palm. Then the edge is extracted from that noise-free image by stretching method and sobel mask Then the fuzzy binarization algorithm is applied to remove any minute noise so that we have only the palm lines and the boundary of the hand. Since the palm line reading is done with major lines, we use the morphological characteristics of the analyzable palm lines and fuzzy inference rules. Experiment verifies that the proposed method is better in visibility and thus more analyzable in palm reading than the old method.

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.700-706
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• 2005

The immigration control system authorizes the immigration of travelers by means of passport inspections such as the judgment of forged passports, the search for a wanted criminal or a person disqualified for immigration, etc. The judgment of forged passports plays an important role in the immigration control system. Therefore, as the pre-phase for the judgment of forged passports, this paper proposed a novel method for the recognition of passport using ART2-based RBF network. The proposed method extracts the area of code and individual codes by applying the Sobel masking, the smearing and the contour tracking algorithm in turn to the passport image. This paper proposed the RBF network that applies the ART2 algorithm to the middle layer, and applied the enhanced RBF network to the recognition of individual codes. The results of the experiments for performance evaluation on the real passport images showed that the proposed method has the better performance compared with other approaches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.684-689
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• 2005

In this paper, we propose car license plate recognition using morphological information and an enhanced neural network. Morphological information on horizontal and vertical edges was used to extract the license plate from a car image. We used a contour tracking algorithm combined with the method of histogram and location information to extract individual characters in the extracted plate. The enhanced neural network is proposed for recognizing them, which has the method of combining the ART-1 and the supervised teaming method. The proposed method has applied to real world car images. The experimental results show that the proposed method has better the extraction rates than the methods with information of the thresholding, the RGB and the HSI, respectively. And the proposed neural network has better recognition performance than the conventional neural networks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.71-73
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• 2017

본 논문에서는 4 방향 윤곽선 추적 기법과 히스토그램 분석 기법을 기반으로 한 개선된 FCM 알고리즘을 적용하여 색조 도플러 초음파 영상에서 상완 동맥의 혈류를 추출하고 분석하는 방법을 제안한다. 제안된 방법에서는 상완 동맥의 혈류를 정확히 추출하기 위해 전처리 과정으로 색조 도플러 초음파 영상 이외의 환자 정보가 있는 영역을 제거한 후, ROI 영역을 추출한다. 추출된 ROI 영역에서 영상의 최대 명암도를 임계치로 설정한 이진화 기법을 적용하여 ROI 영역을 이진화한다. 이진화된 ROI 영역에서 4 방향 윤곽선 추적 기법을 적용하여 상완 동맥이 존재하는 사다리꼴 형태의 영역을 추출한다. 색 정보를 분석한 히스토그램을 이용하여 특징점의 개수를 계산하고 계산된 특징점의 개수를 FCM 알고리즘의 초기 클러스터의 개수로 설정한 후, 추출된 사다리꼴 형태의 영역에 적용하여 양자화 한다. 양자화된 영역 중에서 빨간색으로 분류된 영역을 고혈압 영역으로 추출한다. 제안된 추출 방법을 20개의 색조 도플러 초음파 영상을 대상으로 실험한 결과, 20개의 색조 도플러 초음파 영상에서 18개의 색조 도플러 초음파 영상이 정확히 추출되었다.