• Journal of Astronomy and Space Sciences
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• v.15 no.1
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• pp.175-182
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• 1998

Any classification process using SAR images presupposes the reduction of multiplicative speckle noise, since the variations caused by speckle make it extremely difficult to distinguish between neighboring classes within the feature space. Therefore, several adaptive filter algorithms have been developed in order to distinguish between them. These algorithms aim at the preservation of edges and single scattering peaks, and smooths homogeneous areas as much as possible. This task is rendered more difficult by the multiplicative nature of the speckle noise the signal variation depends on the signal itself. In this paper, LEE(Lee 1908) and R-LEE(Lee 1981) filters using local statistics, local mean and variance, are applied to RADARSAT SAR images. Also, a new method of speckle filtering, EPOS(Edge Preserving Optimal Speckle)(Hagg & Sties 1994) filter based on the statistical properties of speckle noise is described and applied. And then, the results of filtering SAR images with LEE, R-LEE and EPOS filters are compared with mean and median filters.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.25-32
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• 2004

We propose a hierarchical disparity estimation algorithm with edge-preserving energy-based regularization. Initial disparity vectors are obtained from downsampled stereo images using a feature-based region-dividing disparity estimation technique. Dense disparities are estimated from these initial vectors with shape-adaptive windows in full resolution images. Finally, the vector fields are regularized with the minimization of the energy functional which considers both fidelity and smoothness of the fields. The first two steps provide highly reliable disparity vectors, so that local minimum problem can be avoided in regularization step. The proposed algorithm generates accurate disparity map which is smooth inside objects while preserving its discontinuities in boundaries. Experimental results are presented to illustrate the capabilities of the proposed disparity estimation technique.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.562-565
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• 2009

This paper describes an automatic 3-dimensional (3D) segmentation method for 3D CT (Computed Tomography) images using region growing (RG) and edge detection techniques. Specifically, an augmented RG method in which the contours of regions are extracted by a 3D digital edge detection filter is presented. The feature of this method is the capability of preventing the leakage of regions which is a defect of conventional RG method. Experimental results applied to the extraction of teeth from 3D CT data of jaw bones show that teeth are correctly extracted by the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.1000-1009
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• 2007

This paper presents a content adaptive interpolation (CAI) for intra deinterlacing. The CAI consists of three steps: pre-processing, content classification, and adaptive interpolation. There are also three main interpolation methods in our proposed CAI, i.e. modified edge-based line averaging (M-ELA), gradient directed interpolation (GDI), and window matching method (WMM). Each proposed method shows different performances according to spatial local features. Therefore, we analyze the local region feature using the gradient detection and classify each missing pixel into four categories. And then, based on the classification result, a different do-interlacing algorithm is activated in order to obtain the best performance. Experimental results demonstrate that the CAI method performs better than previous techniques.

• Journal of Korean Society of Steel Construction
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• v.12 no.4 s.47
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• pp.363-374
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• 2000

An accurate method is presented for vibrations of rhombic plates having three different combinations of clamped, simply supported, and free edge conditions. A specific feature here is that the analysis explicitly considers the moment singularities that occur in the two opposite corners having obtuse angles of the rhombic plates. Stationary conditions of single-field Lagrangian functional are derived using the Ritz method. Convergence studies of frequencies show that the corner functions accelerate the convergence rate of solutions. In this paper, accurate frequencies and normalized contours of the vibratory transverse displacement are presented for highly skewed rhombic plates, so that a significant effect of corner stress singularities nay be understood.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.204-204
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• 2012

Peierls instability and spin ordering of zigzag graphene nanoribbons (GNR) created on a fully hydrogenated graphene (graphane) are investigated as a function of their width using first-principles density-functional calculations within the generalized-gradient approximation. For the width containing a single zigzag C chain (N=1), we find the presence of a Peierls instability with a bond alternated structure. However, for width greater than N=1, the Peierls distortion is weakened or disappears because of the incommensurate feature of Fermi surface nesting due to the interaction of C chains. Instead, there exists the antiferromagnetic (AFM) spin ordering in which the edge states are ferromagnetically ordered but the two ferromagnetic (FM) edges are antiferromagnetically coupled with each other, showing that electron-lattice coupling and spin ordering in GNR are delicately competing at an extremely thin width of N=2. It is found that, as the width of GNR increases, the energy gain arising from spin ordering is enhanced, but the energy difference between the AFM and FM (where two edge states are ferromagnetically coupled with each other) orderings decreases.

• Journal of Sensor Science and Technology
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• v.10 no.5
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• pp.286-291
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• 2001

We propose a new saliency map model for selecting an attended location in an arbitrary visual scene, which is one of the most important characteristics of human vision system. In selecting an attended location, an edge information can be considered as a feature basis to construct the saliency map. Edge filters are obtained from the independent component analysis(ICA) that is the best way to find independent edges in natural gray scenes. In order to reflect the non-uniform density in our retina, we use a multi-scaled pyramid input image instead of using an original input image. Computer simulation results show that the proposed saliency map model with multi-scale property successfully generates the plausible attended locations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1251-1256
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• 2010

In the transmitting process of image signal processing system, there are several different causes of degradation that have been occuring. The main cause of degradation is attributed to the noise. The most representive method of removing noise of image, which is caused by impulse noise environment, is using the SM filter. At edge, the filter has a special feature which has a tendency to decrease. As a result, we proposed a nonlinear filter using the form of mask and the probability of the impulse noise to restore the image considering edge quality in the impulse noise environment. And through the simulation, we compared with the existings and capabilities.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2558-2562
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• 1999

This paper proposes on the methods of noise removal and edge extraction which is done by eliminating the ambiguities of the image using normalization and minimizing the entropy. Pre-existing methods have their own peculiarities and limitations, such as gray level distributions change very slowly or two regions which having similar gray level distribution are touched. This affects on the post processing such as feature extraction, as a result, this leads to false-recognition or no-recognition. Therefore, this paper proposes on the methods which overcome these problems. Finally, the effectiveness of this paper is demonstrated by several experiments.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.