• Journal of Digital Convergence
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• v.11 no.12
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• pp.295-302
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• 2013

Many reported methods assume that the people in an image or an image sequence have been identified and localization. People detection is one of very important variable to affect for the system's performance as the basis technology about the detection of other objects and interacting with people and computers, motion recognition. In this paper, we present an efficient linear discriminant for multi-view people detection. Our approaches are based on linear discriminant. We define training data with fisher Linear discriminant to efficient learning method. People detection is considerably difficult because it will be influenced by poses of people and changes in illumination. This idea can solve the multi-view scale and people detection problem quickly and efficiently, which fits for detecting people automatically. In this paper, we extract people using fisher linear discriminant that is hierarchical models invariant pose and background. We estimation the pose in detected people. The purpose of this paper is to classify people and non-people using fisher linear discriminant.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.783-788
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• 2003

In this paper, we present a new approach to detect and recognize human face in the image from vision camera equipped on the mobile robot platform. Due to the mobility of camera platform, obtained facial image is small and pose-various. For this condition, new algorithm should cope with these constraints and can detect and recognize face in nearly real time. In detection step, ‘coarse to fine’ detection strategy is used. Firstly, region boundary including face is roughly located by dual ellipse templates of facial color and on this region, the locations of three main facial features- two eyes and mouth-are estimated. For this, simplified facial feature maps using characteristic chrominance are made out and candidate pixels are segmented as eye or mouth pixels group. These candidate facial features are verified whether the length and orientation of feature pairs are suitable for face geometry. In recognition step, pseudo-convex hull area of gray face image is defined which area includes feature triangle connecting two eyes and mouth. And random lattice line set are composed and laid on this convex hull area, and then 2D appearance of this area is represented. From these procedures, facial information of detected face is obtained and face DB images are similarly processed for each person class. Based on facial information of these areas, distance measure of match of lattice lines is calculated and face image is recognized using this measure as a classifier. This proposed detection and recognition algorithms overcome the constraints of previous approach [15], make real-time face detection and recognition possible, and guarantee the correct recognition irregardless of some pose variation of face. The usefulness at mobile robot application is demonstrated.

• Journal of the Korean Chemical Society
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• v.39 no.8
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• pp.643-649
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• 1995

The Menschutkin type reactions of substituted(Z)-benzyl systems with substituted(Y)-pyridines and N,N-dimethyl aniline have been studied by the electro-conductometric method in acetonitrile at 35$^{\circ}C$ and 50$^{\circ}C$. On the plot of $k_{obs}$ versus concentrations of nucleophile under pseudo-first order conditions, 3,$4-(CH_3/O)_2$-benzyl bromide and $4-CH_3O$-benzyl bromide were a positive intercept at zero concentration of nucleophile. The $k_1$ value for each compound was invariant with the different nucleoephile. However, $4-CH_3-$ and other electron withdrawing substituents of benzyl bromides did not show the positive intercept. These results are suggested that the reactions have been proceeding simultaneously and independently for the activated benzyl bromides via direct bimolecular and intimate ion pair intermediate.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.3 s.309
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• pp.39-49
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• 2006

This paper proposes a hand-posture recognition method using reinforcement learning for the performance improvement of vision-based hand-posture recognition. The difficulties in vision-based hand-posture recognition lie in viewing direction dependency and self-occlusion problem due to the high degree-of-freedom of human hand. General approaches to deal with these problems include multiple camera approach and methods of limiting the relative angle between cameras and the user's hand. In the case of using multiple cameras, however, fusion techniques to induce the final decision should be considered. Limiting the angle of user's hand restricts the user's freedom. The proposed method combines angular features and appearance features to describe hand-postures by a two-layered data structure and reinforcement learning. The validity of the proposed method is evaluated by appling it to the hand-posture recognition system using three cameras.

• The Journal of the Acoustical Society of Korea
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• v.34 no.5
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• pp.394-402
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• 2015

CMA (Constant Modulus Algorithm) is one of the well-known algorithms in blind acoustic channel equalization. Generally, CMA converges slowly and the speed of convergence is dependent on a step-size in the CMA procedure. Many researches have tried to speed up the convergence speed by applying a variable step-size to CMA, e.g. the orthogonal projection CMA and algebraic optimal step-size CMA. In this paper, we summarize these two algorithms, and we propose a new CMA with improved convergence performance. The improvement comes from the switching between the orthogonal projection CMA and algebraic optimal step-size CMA. In simulation results, we show the performance improvement in the time invariant channels as well as in time varying channel.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.75-87
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• 2009

We propose in this paper a novel approach to image fusion in which the fusion rule is guided by optimizing an image clarity function. A Genetic Algorithm is used to stochastically select, comparative to the clarity function, the optimum block from among the source images. A novel nested Genetic Algorithm with gifted individuals found through bombardment of genes by the mutation operator is designed and implemented. Convergence of the algorithm is analytically and empirically examined and statistically compared (MANOVA) with the canonical GA using 3 test functions commonly used in the GA literature. The resulting GA is invariant to parameters and population size, and a minimal size of 20 individuals is found to be sufficient in the tests. In the fusion application, each individual in the population is a finite sequence of discrete values that represent input blocks. Performance of the proposed technique applied to image fusion experiments, is characterized in terms of Mutual Information (MI) as the output quality measure. The method is tested with C=2 input images. The results of the proposed scheme indicate a practical and attractive alternative to current multi-focus image fusion techniques.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.221-232
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• 2012

The double-density discrete wavelet transform(DWT) is an improvement upon the critically sampled DWT with important additional properties. It employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. And it is overcomplete by a factor of two. Also, this transformation is nearly shift-invariant. But there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. Proposed method is a DWT that combines the double-density DWT and quincunx sampling, each of which has its own characteristics and advantages. Especially, the quincunx sampling treats the different directions more homogeneously. As a result, since proposed method can generate sub-images of multiple degrees rotated versions, this method provides an improved performance in image processing fields.

• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.216-225
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• 2020

In this paper, broadband underwater propagation channel modeling based on eigenray analysis is discussed. Underwater channels are often formulated in frequency domain time-harmonic signals, which are impractical for simulating broadband signals in time domain. In this regard, time domain modeling of the underwater propagation channel is required for the simulation of broadband signals, for which the eigenray analysis based on ray tracing, resulting in multipath propagation delays in time-domain, is used in this paper. For discrete time system application, the phase, frequency-dependent loss and non-integer sample delays for each eigenray, are approximated by the finite impulse response of the broadband propagation channel.

• Analytical Science and Technology
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• v.12 no.5
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• pp.387-396
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• 1999

The retention behavior of Cot(II)-dithiocarbamate(DTC) chelates in reversed phase high performance liquid chromatography was investigated. Enthalpy and entropy of chelates transfer from the mobile phase to the stationary phase were calculated from retention data using van't Hoff plots. The dependence of In k' on enthalpy was decreased with increasing organic solvent ratio on the mobile phase. The compensation temperatures(${\beta}$) calculated from the slope of $-{\Delta}H^0$ vs In k' were in the range of 756.3-888.5 K. From these results. it was found that the retention mechanism of DTC chelates was invariant under the various temperatures and was largely affected by the solvophobie effect. Liniear relationship between S index and log k' in emprical retention equation, $log\;k^{\prime}=log\;{k_w}^{\prime}-S_{\varphi}$ showed that S index was influenced mainly by the interaction between DTC chelates and the mobile phase.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1490-1501
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• 2016

In this paper, we propose an image-based indoor localization system using parallel distributed computing. In order to reduce computation time for indoor localization, an scale invariant feature transform (SIFT) algorithm is performed in parallel by using Apache Spark. Toward this goal, we propose a novel image processing interface of Apache Spark. The experimental results show that the speed of the proposed system is about 3.6 times better than that of the conventional system.