• The KIPS Transactions:PartD
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• v.14D no.2
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• pp.169-180
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• 2007

This paper discusses a new unsupervised XML document clustering technique based on the function transform and FFT(Fast Fourier Transform). An XML document is transformed into a discrete function based on the hierarchical nesting structure of the elements. The discrete function is, then, transformed into vectors using FFT. The vectors of two documents are compared using a weighted Euclidean distance metric. If the comparison is lower than the pre specified threshold, the two documents are considered similar in the structure and are grouped into the same cluster. XML clustering can be useful for the storage and searching of XML documents. The experiments were conducted with 800 synthetic documents and also with 520 real documents. The experiments showed that the function transform and FFT are effective for the incremental and unsupervised clustering of XML documents similar in structure.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.3 s.303
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• pp.63-72
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• 2005

In this paper, we propose a deformation technique based on Radial Basis Function (RBF) and a blending technique combining the deformed facial component with the original face for a Virtual Aesthetic Surgery (VAS) system. The deformation technique needs the smoothness and the accuracy to deform the fluid facial components and also needs the locality not to affect or distort the rest of the facial components besides the deformation region. To satisfy these deformation characteristics, The VAS System computes the degree of deformation of lattice cells using RBF based on a Free-Form Deformation (FFD) model. The deformation error is compensated by the coefficients of mapping function, which is recursively solved by the Singular Value Decomposition (SVD) technique using SSE (Sum of Squared Error) between the deformed control points and target control points on base curves. The deformed facial component is blended with an original face using a blending ratio that is computed by the Euclidean distance transform. An experimental result shows that the proposed deformation and blending techniques are very efficient in terms of accuracy and distortion.

• Journal of Satellite, Information and Communications
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• v.7 no.2
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• pp.97-103
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• 2012

A very low complexity QRD-M algorithm based on limited search area is proposed for MIMO systems. The conventional QRD-M algorithm calculates Euclidean distance between all constellation symbols and the temporary detection symbol at each layer. We found that performance will not be degraded even if we adaptively restrict the search area of the candidate symbols only to the neighboring points of temporary detection symbol according to the channel condition at each layer. As a channel condition indicator, we employ the channel gain ratio among the layers without necessity of SNR estimation. The simulation results show that the proposed scheme effectively achieves near optimal performance while maintaining the overall average computation complexity much smaller than the conventional QRD-M algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.79-86
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• 2009

This study proposed a method of detecting the facial area by calculating Euclidian distances among skin color elements and extracting the characteristics of the face. The proposed algorithm is composed of light calibration and face detection. The light calibration process performs calibration for the change of light. The face detection process extracts the area of skin color by calculating Euclidian distances to the input images using as characteristic vectors color and chroma in 20 skin color sample images. From the extracted facial area candidate, the eyes were detected in space C of color model CMY, and the mouth was detected in space Q of color model YIQ. From the extracted facial area candidate, the facial area was detected based on the knowledge of an ordinary face. When an experiment was conducted with 40 color images of face as input images, the method showed a face detection rate of 100%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2021-2026
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• 2016

In this paper, a system model for transmission of 3-dimensional (3-D) signals is presented and its performance is analyzed. Unlike 2-D signals, no quadrature form expression for the 3-D signals is available. Exploiting a set of orthogonal basis functions, the 3-D signals are transmitted. As a result of computer simulation using very higher-level signal constellations, the 3-D transmission system has significantly improved error performance as compared with the 2-D system. It is considered that the principal reason for such performance improvement is much increased minimum Euclidean distance (MED) of the 3-D lattice constellations compared with the corresponding 2-D ones. When the MEDs of 2-D and 3-D lattice constellation are compared to confirm the analysis, the MED of 3-D 1024-ary constellation is around 2.6 times larger than that of the quadrature amplitude modulation (QAM). Expanding the constellation size to 4096, the MED of 3-D lattice constellation is increased by 3.2 times of the QAM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.847-852
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• 2010

Text in natural images has a various and important feature of image. Therefore, to detect text and extraction of text, recognizing it is a studied as an important research area. Lately, many applications of various fields is being developed based on mobile phone camera technology. Detecting edge component form gray-scale image and detect an boundary of text regions by local standard deviation and get an connected components using Euclidean distance of RGB color space. Labeling the detected edges and connected component and get bounding boxes each regions. Candidate of text achieved with heuristic rule of text. Detected candidate text regions was merged for generation for one candidate text region, then text region detected with verifying candidate text region using ectilarity characterization of adjacency and ectilarity between candidate text regions. Experctental results, We improved text region detection rate using completentary of edge and color connected component.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.649-654
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• 2005

In this paper, we describe an implementation of real-time face recognition system under ubiquitous computing environments. First, face image is captured by PDA with CMOS camera and then this image with user n and name is transmitted via WLAN(Wireless LAN) to the server and finally PDA receives verification result from the server The proposed system consists of server and client parts. Server uses PCA and LDA algorithm which calculates eigenvector and eigenvalue matrices using the face images from the PDA at enrollment process. And then, it sends recognition result using Euclidean distance at verification process. Here, captured image is first compressed by the wave- let transform and sent as JPG format for real-time processing. Implemented system makes an improvement of the speed and performance by comparing Euclidean distance with previously calculated eigenvector and eignevalue matrices in the learning process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2158-2165
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• 2007

In this paper, a Modified Fuzzy C-Means algorithm with Gaussian Weights(MFCM_GW) is presented for nonlinear blind channel equalization. The proposed algorithm searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function and Gaussian weighted partition matrix instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function(RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a simplex genetic algorithm(GA), a hybrid genetic algorithm(GA merged with simulated annealing(SA): GASA), and a previously developed version of MFCM. It is shown that a relatively high accuracy and fast search speed has been achieved.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.125-131
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• 2019

A vanishing point is a point on an image to which parallel lines projected from a real space gather. A vanishing point in a road space provides important spatial information. It is possible to improve the position of an extracted lane or generate a depth map image using a vanishing point in the road space. In this paper, we propose a method of detecting vanishing points on images taken from a vehicle's point of view using Deep Neural Network (DNN) and Histogram of Oriented Gradient (HoG). The proposed algorithm is divided into a HoG feature extraction step, in which the edge direction is extracted by dividing an image into blocks, a DNN learning step, and a test step. In the learning stage, learning is performed using 2,300 road images taken from a vehicle's point of views. In the test phase, the efficiency of the proposed algorithm using the Normalized Euclidean Distance (NormDist) method is measured.

• Convergence Security Journal
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• v.17 no.5
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• pp.11-18
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• 2017

Now the ways in which information is exchanged by computers are changing, a variety of this information exchange method also requires corresponding change of responding to an illegal attack. Among these illegal attacks, the IP spoofing attack refers to the attack whose process are accompanied by DDoS attack and resource exhaustion attack. The way to detect an IP spoofing attack is by using traceback information. The basic traceback information analysis method is implemented by comparing and analyzing the normal router information from client with routing information existing in routing path on the server. There fore, Such an attack detection method use all routing IP information on the path in a sequential comparison. It's difficulty to responding with rapidly changing attacks in time. In this paper, all IP addresses on the path to compute in a coordinate manner. Based on this, it was possible to analyze the traceback information to improve the number of traceback required for attack detection.