• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1088-1097
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• 2003

In this paper, we propose a method that improves the snakes algorithm well known as previously active contour model. Generally, the previous snakes algorithm applied to the 2-D images doesn't get the good results due to the influences about other objects adjacent to contour of object to be extracted. Users directly set the initial snakes points near to the contour of the object to get better results. In this paper, using the disparity information of the stereo images, a new algorithm of the object segmentation is proposed to reduce the influences adjacent to the contour of object. Users can establish initial snakes points automatically from the setting of the interested regions.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.753-762
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• 2006

The Snakes and GVF used to find object edges dynamically have assigned their initial contour arbitrarily. If the initial contours are located in the neighboring regions of object edges, Snakes and GVF can be close to the true boundary. If not, these will likely to converge to the wrong result. Therefore, this paper proposes a new initialization of Snakes and GVF using convex hull approximation, which initializes the vertex of Snakes and GVF as a convex polygonal contour near object edges. In simulation result, we show that the proposed algorithm has a faster convergence to object edges than the existing methods. Our algorithm also has the advantage of extracting whole edges in real images.

• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.69-73
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• 1999

In this paper, an algorithm based on Snakes is proposed to detect the boundary of 3D images. From the first-slice MR image, the boundary of an object is detected manually. The detected boundary points are used as initial control points for detecting the boundary of the next MR image. To detect the boundary from the rest of MR images automatically, an energy term using spatial correlation between adjacent images is added to the Greedy Snakes energy formulation. A measure of shape similarity called BMD was used to evaluate the accuracy of the proposed algorithm. The average BMD value for the proposed algorithm's result is higher than Greedy algorithm's showing the utility of the proposed method.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.236-239
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• 1997

Snakes is an active contour model or representing image contours. To detect chest boundary on thoracic MRI sequences, we proposed a method based on modified greedy algorithm. Because thoracic MRI sequences have a spatial correlation, we added energy term related with spatial correlation to Snakes energy formulation. A measure of shape similarity called the BMD was used to evaluate the accuracy of the algorithm. The average BMD value or the modified algorithm's result is higher than greedy algorithm's.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2798-2800
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• 2003

Active contour models(called Snakes) are methods for the image segmentation. Many researchers have developed snake algorithms and then published such as GVF, GGF snake. In this paper, we present a pre-process for GGF snake algorithm. This process removes noise so that snakes can flow smoothly. In experiment, we compared a image removed noise with a image corrupted by noise. In result, the pre-process produced a good image for GGF Snake and is necessary.

• 한국HCI학회:학술대회논문집
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• 2008.02c
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• pp.19-24
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• 2008

This paper presents a physically-based haptic rendering algorithm for a deformable object based on visual information about the intervention between a tool and a real object in a remote place. The physically-based model of a deformable object is created from the mechanical properties of the object and the captured image obtained with a CCD camera. When a slave system exerts manipulation tasks on a deformable object, the reaction force for haptic rendering is computed using boundary element method. Snakes algorithm is used to obtain the geometry information of a deformable object. The proposed haptic rendering algorithm can provide haptic feedback to a user without using a force transducer in a teleoperation system.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.705-716
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• 2002

This paper proposes a method which visualizes MRI head data in 3 dimensions with direct volume rendering. Though surface rendering is usually used for MRI data visualization, it has some limits of displaying little speckles because it loses the information of the speckles in the surfaces while acquiring the information. Direct volume rendering has ability of displaying little speckles, but it doesn't treat MRI data because of the data features of MRI. In this paper, we try to visualize MRI head data in 3 dimensions as follows. First, we separate the brain region from the head region of MRI head data, next increase the pixel level of the brain region, then combine the brain region with the increased pixel level and the head region without brain region, last visualizes the combined MRI head data with direct volume rendering. We segment the brain region from head region based on histogram threshold, morphology operations and snakes algorithm. The proposed segmentation method shows 91~95% similarity with a hand segmentation. The method rather clearly visualizes the organs of the head in 3 dimensions.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.30-34
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• 1998

Path Planning is one of the important fields in robot technologies. Local path planning may be done in on-line modes while recognizing an environment of robot by itself. In dynamic environments to obtain fluent information for environments vision system as a sensing equipment is a one of the most necessary devices for safe and effective guidance of robots. If there is a predictor that tells what future sensing outputs will be, robot can respond to anticipated environmental changes in advance. The tracking of obstacles has a deep relationship to the prediction for safe navigation. We tried to deal with active contours, that is snakes, to find out the possibilities of stable tracking of objects in image plane. Snakes are defined based on energy functions, and can be deformed to a certain contour form which would converge to the minimum energy states by the forces produced from energy differences. By using point algorithm we could have more speedy convergence time because the Brent's method gives the solution to find the local minima fast. The snake algorithm may be applied to sequential image frames to track objects in the images by these characteristics of speedy convergence and robust edge detection ability.

• Journal of the Korea Society of Computer and Information
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• v.3 no.1
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• pp.81-94
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• 1998

In order to extract the contour of interesting object in the image, Kass suggested the Active Contour Model called "Snakes". Snakes is a model which defines the contour of image energy. It also can find the contour of object by minimizing these energy functions. The speed of this model is slow and this model is sensitive of initialization. In order to improve these problems, Gunn extracted the accurate contour by using two initialization. and operated to less sensitive of initialization. This method could extract more accurate contour than the existing method, but it had no effect in the speed and it was sensitive of noise. This paper applied to the Energy Minimization Algorithm about only the pixel within the window applying the window of 8$\times$8 size at each contour point consisting Snakes in order to solve these problems. The method offered in this paper is applied to extract the contour of original image and cup image added to gaussian noise. By tracking the face using this offered method, it is applied to virtual reality and motion tracking. tracking.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2809-2815
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• 1999

Level set, and active contour(snakes) models are extensively used for image segmentation or shape extraction in computer vision. Snakes utilize the energy minimization concepts, and level set is based on the curve evolution in order to extract contours from image data. In general, these two models have their own drawbacks. For instance, snake acts pooly unless it is placed close to the wanted shape boundary, and it has difficult problem when image has multiple objects to be extracted. But, level set method is free of initial curve position problem, and has ability to handle topology of multiple objects. Nevertheless, level set method requires much more calculation time compared to snake model. In this paper, we use good points of two described models and also apply multi resolution algorithm in order to speed up the process without decreasing the performance of the shape extraction.