• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.153-156
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• 2003

This paper proposes a video tracking method for a deformable moving object using an active contour model. In order to decide the convergent directions of the contour points automatically, a new energy function based on a frame difference map and an updating rules of the frame difference map are presented. Experimental results on a set of synthetic and real image sequences showed that the proposed method can fully track a speedy deformable object while extracting the boundary of the object exactly in every frame.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.5
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• pp.332-340
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• 2015

Acoustic emission (AE) is an effective nondestructive test that uses transient elastic wave generated by the rapid release of energy within a material to detect any further growth or expansion of existing defects. Over the past decades, because of environmental issues, the use of compressed natural gas (CNG) as an alternative fuel for vehicles is increasing because of environmental issues. For this reason, the importance and necessity of detecting defects on a CNG fuel tank has also come to the fore. The conventional AE method used for source location is highly affected by the wave speed on the structure, and this creates problems in inspecting a composite CNG fuel tank. Because the speed and dispersion characteristics of the wave are different according to direction of structure and laminated layers. In this study, both the conventional AE method and the energy based contour map method were used for source location. This new method based on pre-acquired D/B was used for overcoming the limitation of damage localization in a composite CNG fuel tank specimen which consists of a steel liner cylinder overwrapped by GFRP. From the experimental results, it is observed that the damage localization is determined with a small error at all tested points by using the energy based contour map method, while there were a number of mis-locations or large errors at many tested points by using the conventional AE method. Therefore, the energy based contour map method used in this work is more suitable technology for inspecting composite structures.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.153-163
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• 2004

This paper presents a video tracking method for a deformable moving object using an active contour model in the image sequences. It is quite important to decide the local convergence directions of the contour points for correctly extracting the boundary of the moving object with deformable shape. For this purpose, an energy function for the active contour model is newly proposed by adding a directional energy term using a frame difference map to tile Greedy algorithm. In addition, an updating rule of tile frame difference map is developed to encourage the stable convergence of the contour points. Experimental results on a set of synthetic and real image sequences showed that the proposed method can fully track the deformable object while extracting the boundary of the object elaborately in every frame.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.901-911
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• 2009

In this paper, we propose a construction technique of two-level composite gradient map to automatically track a face with large movement in successive frames. Our method is composed of three main steps. First, the gradient maps with two-level resolution are generated for fast convergence of active contour. Second, to recognize the variations of face between successive frames and remove the neighbor background, weighted composite gradient map is generated by combining the composite gradient map and difference mask of previous and current frames. Third, to prevent active contour from converging local minima, the energy slope is generated by using closing operation. In addition, the fast closing operation is proposed to accelerate the processing time of closing operation. For performance evaluation, we compare our method with previous active contour model-based face tracking methods using a visual inspection, robustness test and processing time. Experimental results show that our method can effectively track the face with large movement and robustly converge to the optimal position even in frames with complicated background.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.7-21
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• 2019

In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.33-45
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• 2011

In this paper, we present a method for extracting video objects efficiently by using the modified graph cut algorithm based on contour information. First, we extract objects at the first frame by an automatic object extraction algorithm or the user interaction. To estimate the objects' contours at the current frame, motion information of objects' contour in the previous frame is analyzed. Block-based histogram back-projection is conducted along the estimated contour point. Each color model of objects and background can be generated from back-projection images. The probabilities of links between neighboring pixels are decided by the logarithmic based distance transform map obtained from the estimated contour image. Energy of the graph is defined by predefined color models and logarithmic distance transform map. Finally, the object is extracted by minimizing the energy. Experimental results of various test images show that our algorithm works more accurately than other methods.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1315-1318
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• 2003

In this paper, a neural network based approach using a self-organizing feature map is proposed for the segmentation of X ray images. A number of algorithms based on such approaches as histogram analysis, region growing, edge detection and pixel classification have been proposed for segmentation of general images. However, few approaches have been applied to X ray image segmentation because of blur of the X ray image and vagueness of its edge, which are inherent properties of X ray images. To this end, we develop a new model based on the neural network to detect objects in a given X ray image. The new model utilizes Mumford-Shah functional incorporating with a modified adaptive SOFM. Although Mumford-Shah model is an active contour model not based on the gradient of the image for finding edges in image, it has some limitation to accurately represent object images. To avoid this criticism, we utilize an adaptive self organizing feature map developed earlier by the authors.[1] It's learning rule is derived from Mumford-Shah energy function and the boundary of blurred and vague X ray image. The evolution of the neural network is shown to well segment and represent. To demonstrate the performance of the proposed method, segmentation of an industrial part is solved and the experimental results are discussed in detail.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.148-157
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• 2012

Recently, people are getting more interested in green energy resource and environment friendly energy resource due to the lack of energy and global warming. This study produced a solar energy resource map using LiDAR(Light Detection And Ranging) data to check if it is utilized for spatial information technology and solar energy sectors that people pay more attentions to as new recycling energy. This study assigned Ulleungdo(Island) located in Gyeongsangbuk-do as a target area. This study created the contour line with 1 meter by newly photographing LiDAR and data processing. And using this contour line, this study built DEM(Digital Elevation Model) data with 1 meter. The incidence range depending on the altitude and azimuth of sun using DEM data is used to evaluate solar energy resource. This is expected to suggest an accurate method to evaluate more reliable and more precise information of new recycling energy resource by producing solar energy resource map based on accurate and precise spatial resolution data with 1 meter level.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.5
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• pp.391-398
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• 2016

Acoustic emission (AE) is one of the most powerful techniques for detecting damages and identify damage location during operations. However, in case of the source location technique, there is some limitation in conventional AE technology, because it strongly depends on wave speed in the corresponding structures having heterogeneous composite materials. A compressed natural gas(CNG) pressure vessel is usually made of carbon fiber composite outside of vessel for the purpose of strengthening. In this type of composite material, locating impact damage sources exactly using conventional time arrival method is difficult. To overcome this limitation, this study applied the previously developed Contour D/B map technique to four types of CNG storage tanks to identify the source location of damages caused by external shock. The results of the identification of the source location for different types were compared.

• Korean Journal of Materials Research
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• v.12 no.1
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• pp.44-47
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• 2002

DV(Discrete Variation)-X${\alpha}$ cluster calculation was employed to calculate the electronic states of ${\gamma}'- Fe_4N$ which was one of iron nitride phases synthesized from plasma ion nitriding to improve surface hardness and wear resistance. The result of calculated electron density of states for Fe was similar to the result of band calculation. The cluster used for calculation of electronic states of ${\gamma}'-Fe_4N$ was based on $Fe_{14}N$ cluster which comprises 15 atoms. Finally the electronic states of ${\gamma}'- Fe_4N$ such as net-charge, band order, energy level, electron wave-function, and contour map for electron density were derived by the calculation.