• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.21-29
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• 2011

At existing skin detection methods using skin color information defined based on the prior knowldege, threshold value to be used at the stage of dividing the backround and the skin region was decided on a subjective point of view through experiments. Also, threshold value was selected in a passive manner according to their background and illumination environments in these existing methods. These existing methods displayed a drawback in that their performance was fully influenced by the threshold value estimated through repetitive experiments. To overcome the drawback of existing methods, this paper propose a skin region detection method using a histogram approximation based on the mean shift algorithm. The proposed method is to divide the background region and the skin region by using the mean shift method at the histogram of the skin-map of the input image generated by the comparison of the similarity with the standard skin color at the CbCr color space and actively finding the maximum value converged by brightness level. Since the histogram has a form of discontinuous function accumulated according to the brightness value of the pixel, it gets approximated as a Gaussian Mixture Model (GMM) using the Bezier Curve method. Thus, the proposed method detects the skin region by using the mean shift method and actively finding the maximum value which eventually becomes the dividing point, not by using the manually selected threshold value unlike other existing methods. This method detects the skin region high performance effectively through experiments.

• Journal of Korea Multimedia Society
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• v.8 no.1
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• pp.27-33
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• 2005

In this paper, an effective skeleton method is proposed in order to obtain an enhanced digital image of skeleton line. The binary image using the threshold values is applied in the preprocessing stage and then The proposed method is applied to obtain the improved image of skeleton line. We used the existing skeleton methods and SPTA(Shin's Parallel Thinning Algorithm) method for the comparison. The demerits of the existing skeleton methods have a result of noise branch, expansion and contraction. and then we are proposed a SPTA method.

• Speech Sciences
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• v.7 no.4
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• pp.41-47
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• 2000

This paper concerns an effective text-prompted speaker verification method to increase the performance of speaker verification. While various speaker verification methods have already been developed, their effectiveness has not yet been formally proven in terms of achieving an acceptable performance level. It is also noted that the traditional methods were focused primarily on single, prompted utterance for verification. This paper, instead, proposes sequential decision method using variable threshold focused at handling two utterances for text-prompted speaker verification. Experimental results show that the proposed speaker verification method outperforms that of the speaker verification scheme without using the sequential decision by a factor of up to 3 times. From these results, we show that the proposed method is highly effective and achieves a reliable performance suitable for practical applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.627-634
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• 2006

We have proposed the methods how to control the slope of CMOS inverter's characteristic and how to shift it in y axis. We control the MOS transistor threshold voltage for these methods. By observing that two transistors are in saturation region at the center of the CMOS inverter's characteristic, we have presented how to make the characteristic for one pole neuron. The circuit level simulation is used for verifying the proposed method. PSpice(OrCAD Co.) is used for circuit level simulation.

• Journal of Electrical Engineering and Technology
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• v.7 no.5
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• pp.797-806
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• 2012

Fault detection and isolation (FDI) algorithms provide fault monitoring methods in GPS measurement to isolate abnormal signals from the GPS satellites or the acquired signal in receiver. In order to monitor the occurred faults, FDI generates test statistics and decides the case that is beyond a designed threshold as a fault. For such problem of fault detection and isolation, this paper presents and evaluates position domain integrity monitoring methods by formulating various pseudorange prediction methods and investigating the resulting test statistics. In particular, precise measurements like carrier phase and Doppler rate are employed under the assumption of fault free carrier signal. The presented position domain algorithm contains the following process; first a common pseudorange prediction formula is defined with the proposed variations in pseudorange differential update. Next, a threshold computation is proposed with the test statistics distribution considering the elevation angle. Then, by examining the test statistics, fault detection and isolation is done for each satellite channel. To verify the performance, simulations using the presented fault detection methods are done for an ideal and real fault case, respectively.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.459-466
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• 2004

In this paper, an effective skeleton method is proposed in order to obtain an enhanced digital image of skeleton line. The binary image using the threshold values is applied in the preprocessing stage and then the modified parallel processing method is applied to obtain the improved image of skeleton line. The existing skeleton methods are Rutovitz, Steiabelli and other five skeleton methods. In the digital process of skeleton line, the major problem caused by these methods is elongated lines and noise branches of the processed image. In this study, however, such noises are deleted first by the modified parallel processing step of the proposed method. Then a pixel is compared to its eight neighbor pixels. if its neighbor pixels are in one of the eight conditions, the central pixel is deleted. As a result, the quality of the skeleton is better then those produced by the existing skeleton methods.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.483-494
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• 2013

The importance of financial risk management has been highlighted after several recent incidences of global financial crisis. One of the issues in financial risk management is how to measure the risk; currently, the most widely used risk measure is the Value at Risk(VaR). We can consider to estimate VaR using extreme value theory if the financial data have heavy tails as the recent market trend. In this paper, we study estimations of VaR using Peaks over Threshold(POT), which is a common method of modeling fat-tailed data using extreme value theory. To use POT, we first estimate parameters of the Generalized Pareto Distribution(GPD). Here, we compare three different methods of estimating parameters of GPD by comparing the performance of the estimated VaR based on KOSPI 5 minute-data. In addition, we simulate data from normal inverse Gaussian distributions and examine two parameter estimation methods of GPD. We find that the recent methods of parameter estimation of GPD work better than the maximum likelihood estimation when the kurtosis of the return distribution of KOSPI is very high and the simulation experiment shows similar results.

• Journal of Animal Science and Technology
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• v.44 no.1
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• pp.31-38
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• 2002

Interval mapping using microsatellite markers was employed to detect quantitative trait loci (QTL) in the experimental cross between Berkshire and Yorkshire pigs. In order to derive critical values (CV) for test statistics for declaring significance of QTL, permutation test (PT) of Churchill and Doerge method(1994) and the analytical method(LK) of Lander and Kruglyak(1995) were used by each trait and chromosome. 525 $F_2$ progeny phenotypes of five traits(carcass weight, loin eye area, marbling score, cholesterol content, last back fat thickness) and genotypes of 125 markers covering the genome were used. Data were analyzed by line cross regression interval mapping with an F-test every by 1cM. PT CV were based on 10,000 permutations. CV at genome-wise test were 10.5 for LK and ranged from 8.1 to 8.3 for PT, depending on the trait. CV, differed substantially between methods, led to different numbers of quantitative trait loci (QTL) to be detected. PT results in the least stringent CV compared at the same % level.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.276-286
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• 2013

SVD-based deconvolution algorithm has been known as the most effective technique for CT perfusion image analysis. In this algorithm, in order to reduce noise effects, SVD coefficients smaller than a certain threshold are removed. As the truncation threshold, either a fixed value or a variable threshold yielding a predetermined OI (oscillation index) is frequently employed. Each of these two thresholding methods has an advantage to the other either in accuracy or efficiency. In this paper, we propose a Monte Carlo simulation method to evaluate the accuracy of the two methods. An extension of the proposed method is presented as well to measure the effects of image smoothing on the accuracy of the thresholding methods. In this paper, after the simulation method is described, experimental results are presented using both simulated data and real CT images.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.931-939
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• 2011

In practice, thresholds are determined by the two subjective assessment methods in a generalized pareto distribution of mean extreme function(MEF-graph) or Hill-graph. To remedy the problem of subjectiveness of these methods, we propose an alternative method to determine the threshold based on the robust statistics. We compared the MEF-graph, Hill-graph and our method through VaRs on the Korean stock market data from January 5, 1987 to August 3, 2009. As a result, the VaR based on the proposed method is not much different from the existing methods, and the standard deviation of VaR for our method was the smallest. The results show that our method can be a promising alternative to determine thresholds of the generalized pareto distributions.