• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.41-50
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• 2004

Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video objects from video sequences. Segmentation algorithms can largely be classified into two different categories: automatic segmentation and user-assisted segmentation. In this paper, we propose a new user-assisted image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is, therefore, applicable to images of complex background. We can also compensate for limitations of the shape matrix with a dynamic graph search algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.39-46
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• 2007

Research on human identification in ubiquitous environment has recently attracted a lot of attention. As one of those research, gait recognition is an efficient method of human identification using physical features of a walking person at a distance. In this paper, we present a human shape extraction and tracking for gait recognition using geodesic active contour models(GACMs) combined with mean shift algorithm The active contour models (ACMs) are very effective to deal with the non-rigid object because of its elastic property. However, they have the limitation that their performance is mainly dependent on the initial curve. To overcome this problem, we combine the mean shift algorithm with the traditional GACMs. The main idea is very simple. Before evolving using level set method, the initial curve in each frame is re-localized near the human region and is resized enough to include the targe region. This mechanism allows for reducing the number of iterations and for handling the large object motion. The proposed system is composed of human region detection and human shape tracking modules. In the human region detection module, the silhouette of a walking person is extracted by background subtraction and morphologic operation. Then human shape are correctly obtained by the GACMs with mean shift algorithm. In experimental results, the proposed method show that it is extracted and tracked efficiently accurate shape for gait recognition.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.3-5
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• 2005

Vessel boundary detection and modeling is a difficult but a necessary task in analyzing the mechanics of inflammation and the structure of the microvasculature. In this paper we present a method of analyzing the structure by means of an active contour model(using GVF Snake) for vessel boundary detection and 3D reconstruction. For this purpose we used a virtual vessel model and produced a phantom model. From these phantom images we obtained the contours of the vessel by GVF Snake and then reconstructed a 3D structure by using the coordinates of snakes.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.335-336
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• 2006

In this paper, we propose an active shape image segmentation method for three-dimensional(3-D) medical images using a generation method of the 3-D shape model. The proposed method generates the shape model using a distance transform and a tetrahedron method for landmarking. After generating the 3-D model, we extend the training and segmentation processes of 2-D active shape model(ASM) and improve the searching process. The proposed method provides comparative results to 2-D ASM, region-based or contour-based methods. Experimental results demonstrate that this algorithm is effective for a semi-automatic segmentation method of 3-D medical images.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.35-46
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• 2006

The dynamic change of background and moving objects is an important factor which causes the problem of occlusion in tracking moving objects. The tracking accuracy is also remarkably decreased in the presence of occlusion. We therefore propose an active fusion model which is robust against partial occlusions that are occurred by background and other objects. The active fusion model is consisted of contour-based md region-based snake. The former is a conventional snake model using contour features of a moving object and the latter is a regional snake model which considers region features inside its boundary. First, this model classifies total occlusion into contour and region occlusion. And then it adjusts the confidence of each model based on calculating the location and amount of occlusion, so it can overcome the problem of occlusion. Experimental results show that the proposed method can successfully track a moving object but the previous methods fail to track it under partial occlusion.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.77-89
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• 2009

Visual tracking technique is one of the essential things which are very important in the major fields of modern society. While contour tracking is especially necessary technique in the aspect of its fast performance with target's external contour information, it sometimes fails to track target motion because it is affected by the surrounding edges around target and weak egdes on the target boundary. To overcome these weak points, in this research it is suggested that PDMs can be obtained by generating the virtual 6-DOF motions of the mobile robot with a CCD camera and the image tracking system which is robust to the local minima around the target can be configured by constructing Active Shape Model in modular base. To show the effectiveness of the proposed method, the experiment is performed on the image stream obtained by a real mobile robot and the better performance is confirmed by comparing the experimental results with the ones of other major tracking techniques.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.829-840
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• 2013

In this paper, we propose a new lung segmentation method for chest x-ray images which can take both global and local properties into account. Firstly, the initial lung segmentation is computed by applying the active shape model (ASM) which keeps the shape of deformable model from the pre-learned model and searches the image boundaries. At the second segmentation stage, we also applied the localizing region-based active contour model (LRACM) for correcting various regional errors in the initial segmentation. Finally, to measure the similarities, we calculated the Dice coefficient of the segmented area using each semiautomatic method with the result of the manually segmented area by a radiologist. The comparison experiments were performed using 5 lung x-ray images. In our experiment, the Dice coefficient with manually segmented area was $95.33%{\pm}0.93%$ for the proposed method. Effective segmentation methods will be essential for the development of computer-aided diagnosis systems for a more accurate early diagnosis and prognosis regarding lung cancer in chest x-ray images.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.492-501
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• 2005

In this paper, we proposed the new segmentation method of optic nerve head and optic cub to consider the depth of optic nerve head on stereo fundus image. We analyzed the error factor of stereo matching on stereo fundus image, and compensated them. For robust extraction of optic nerve head and optic cub, we proposed the modified active contour model to consider the 3D depth of optic nerve head. As experiment result to various stereo fundus images, we confirmed that proposed method can segment optic nerve head and optic cup effectively.

• The Journal of Korean Academy of Prosthodontics
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• v.33 no.1
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• pp.13-23
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• 1995

The purpose of this study is to inquire about the effects of individual tray design and impression method on the border extension and contour of denture. 10 students at the dentistry college who have normal occlusion and symmetric facial form and normal facial muscle activity were selected. The tray was designed three types (large, medium, small tray). After border molding was done by dentist and operator, final impression was taken. The length of impression body and width of border were measured by a vernier caliper on the cast. The obtained results were as follows : 1. As the tray border was shortened, the length of impression body and width of border was short (P<0.01). 2. When the impression was taken with the small tray, the length of impression body was short in passive border molding than active border molding. 3. When the medium tray was used, the width of impression body was short in passive border molding than active border molding.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.101-109
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• 2014

It is an essential element for the establishment of image processing related systems to find the exact contour from the image of an arbitrary object. In particular, if a vision system is established to inspect the products in the automated production process, it is very important to detect the contours for standardized shapes such lines and curves. In this paper, we propose a prototype adaptive dynamic contour model, p-Snake with improved contour extraction algorithms by adding the prototype energy. The proposed method is to find the initial contour by applying the existing Snake algorithm after Sobel operation is performed for prototype analysis. Next, the final contour of the object is detected by analyzing prototypes such as lines and circles, defining prototype energy and using it as an additional energy item in the existing Snake function on the basis of information on initial contour. We performed experiments on 340 images obtained by using an environment that duplicated the background of an industrial site. It was found that even if objects are not clearly distinguished from the background due to noise and lighting or the edges being insufficiently visible in the images, the contour can be extracted. In addition, in the case of similarity which is the measure representing how much it matches the prototype, the prototype similarity of contour extracted from the proposed p-ACM is superior to that of ACM by 9.85%.