• 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.17 no.5
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• pp.566-572
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• 2014

The hippocampus has been known as one of the most important structure related to many neurological disorders, such as Alzheimer's disease. This paper presents the snake model to segment hippocampus from brain MRI. The snake model or active contour model is widely used in medical image processing fields, especially image segmentation they look onto nearby edge, localizing them accurately. We applied a snake model on brain MRI. Then we compared our results with an active shape approach. The results show that hippocampus was successfully segmented by the snake model.

• 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.

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.641-650
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• 2005

In this parer, curve stopping function based on the CT number of lung parenchyma from CT lung images is proposed to detect lung region in replacement of conventional edge indication function in geodesic active contour model. We showed that the proposed method was able to detect lung region more effectively than conventional method by applying three kinds of measurement numerically. And, we verified the effectiveness of proposed method visually by observing the detection Procedure on actual CT images. Because lung parenchyma region could be precisely detected from actual EBCT (electron beam computer tomography) lung images, we were sure that the Proposed method could aid to early diagnosis of lung disease and local abnormality of function.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.651-659
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• 2000

It is very important to extract the heart region in the medical images. In this paper, we present the automatic heart region extraction in the EBT (electron beam tomography) images. We use contrast thresholding, anatomic knowledge, and mathematical morphology to extract the heart region. Using these results, we applied the active contour models (snakes) to search the exact region. We analyzed the experimental results by comparing the results with the results made by medical experts.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.75-85
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• 2002

In this paper, we propose an efficient method for recognizing lip. Lip is localized by using the shape of lip and the pixel values around lip contour. The shape of lip is represented by a statistically based active shape model which learns typical lip shape from a training set. Because this model is affected by the initial position, we use a boundary between upper and lower lip as initial position for searching lip. The boundary is localized by using a weighted vector based on lip's shape. The experiments have been performed for many images, and show very encouraging result.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.10
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• pp.902-909
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• 2015

In this paper, monovision based relative navigation for a satellite proximity operation is studied. The chaser satellite only uses one camera sensor to observe the target satellite and conducts image tracking to obtain the target pose information. However, by using only mono-vision, it is hard to get the depth information which is related to the relative distance to the target. In order to resolve the well-known difficulty in computing the depth information with the use of a single camera, the active contour method is adopted for the image tracking process. The active contour method provides the size of target image, which can be utilized to indirectly calculate the relative distance between the chaser and the target. 3D virtual reality is used in order to model the space environment where two satellites make relative motion and produce the virtual camera images. The unscented Kalman filter is used for the chaser satellite to estimate the relative position of the target in the process of glideslope approaching. Closed-loop simulations are conducted to analyze the performance of the relative navigation with the active contour method.

• Journal of the Semiconductor & Display Technology
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• v.15 no.2
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• pp.61-65
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• 2016

Facial feature detection is a fundamental function in the field of computer vision such as security, bio-metrics, 3D modeling, and face recognition. There are many algorithms for the function, active shape model is one of the most popular local texture models. This paper addresses issues related to face detection, and implements an efficient extraction algorithm for extracting the facial feature points to use on iOS platform. In this paper, we extend the original ASM algorithm to improve its performance by four modifications. First, to detect a face and to initialize the shape model, we apply a face detection API provided from iOS CoreImage framework. Second, we construct a weighted local structure model for landmarks to utilize the edge points of the face contour. Third, we build a modified model definition and fitting more landmarks than the classical ASM. And last, we extend and build two-dimensional profile model for detecting faces within input images. The proposed algorithm is evaluated on experimental test set containing over 500 face images, and found to successfully extract facial feature points, clearly outperforming the original ASM.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.2
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• pp.97-111
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• 1995

In this paper, we investigate path compensation scheme for the machining errors due to tool deflection in 2D contour machining. The significance of the deflection error is first shown by experiments, and a direct compensation scheme is sought. In the presented scheme, the tool path is evaluated and correcte based on the instantaneous deflection force model, until the desired contour can be obtained under the presence of tool deflection in actual machining. In the sense that the developed method estimates and compensates the machining errors via modifying the tool path, it is distinguished from the previous approach based on geometric simulation and cutting simulation. Further, it can be viewed as a direct and active method toward direct shape control in CNC machining. Simulation results are included to show the validity and adequacy of the path-modification scheme under various cutting conditions.

• 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.