• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.7-10
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• 2000

There are many Problems such as low detection ratio, velocity and increase of false hit ratio on the detection of gradual scene changes with the previous shot transition detection algorithms. In this paper, we Propose an improved dissolve detection method using color information on low-frequency subband and edge elements on high-frequency subband. The Possible dissolve transition are found by analyzing the edge change ratio in the high-frequency subband with edge elements of each direction. Using the double chromatic difference on the lowest frequency subband, we have the improvement of the dissolve detection ratio. The simulation results show that the performance of the proposed algorithm is better than the conventional one for dissolve detection on a diverse set of uncompressed video sequences.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1081-1088
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• 2013

Hyperspectral cameras acquire reflectance values at many different wavelength bands. Dimensions tend to increase because spectral information is stored in each pixel. Several attempts have been made to reduce dimensional problems such as the feature selection using Adaboost and dimension reduction using the Simulated Annealing technique. We propose a novel material detection method that consists of four steps: feature band selection, feature extraction, SVM (Support Vector Machine) learning, and target and specific region detection. It is a combination of the band ratio method and Simulated Annealing algorithm based on detection rate. The experimental results validate the effectiveness of the proposed feature selection and band ratio method.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1091-1098
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• 2006

Park et al.(2005) and Choi et al.(2006) studied quick detection of variance change point for time series data in progress. For efficient detection they used moving variance ratio equipped with two tuning parameters; information tuning parameter p and lag tuning parameter q. In this paper, the moving variance ratio is studied under harsh conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.532-540
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• 2005

In this paper, a sequential detection scheme is proposed as a combination of a novel weak-signal and a locally optimum(LO) detection schemes. In Part 1, we propose a novel sequential detection scheme for weak signals and show some interesting threshold properties and examples. In Part 2, the performance of the proposed sequential detection scheme is compared with that of the fixed sample size(FSS) test, sequential probability ratio test (SPRT), and truncated sequential probability ratio test(TSPRT).

• Speech Sciences
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• v.10 no.1
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• pp.95-105
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• 2003

This paper describes a new parameter for voice activity detection which serves as a front-end part for automatic speech recognition systems. The new parameter called run-ratio is derived from the runs test statistic which is used in the statistical test for randomness of a given sequence. The run-ratio parameter has the property that the values of the parameter for the random sequence are about 1. To apply the run-ratio parameter into the voice activity detection method, it is assumed that the samples of an inputted audio signal should be converted to binary sequences of positive and negative values. Then, the silence region in the audio signal can be regarded as random sequences so that their values of the run-ratio would be about 1. The run-ratio for the voiced region has far lower values than 1 and for fricative sounds higher values than 1. Therefore, the parameter can discriminate speech signals from the background sounds by using the newly derived run-ratio parameter. The proposed voice activity detector outperformed the conventional energy-based detector in the sense of error mean and variance, small deviation from true speech boundaries, and low chance of missing real utterances

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.1027-1035
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• 2005

In this paper, the performance of the sequential detection scheme proposed in Part 1 is compared with that of the fixed sample size (FSS) test, sequential probability ratio test (SPRT), and truncated sequential probability ratio test (TSPRT). The proposed sequential detection scheme requires less complexity and, in most cases, smaller sample size than the SPRT. It is also observed that the proposed sequential detection scheme has always lower complexity and smaller sample size than the FSS test and TSPRT.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.229-232
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• 2009

Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see real-time operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST Company. Thus, our algorithm in the paper can be useful in PMP or other portable players.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1998.06a
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• pp.535-537
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• 1998

In this paper, we devised a pulse rate detection system to provide basic clinical index of cold-hot diagnosis of oriental medicine. The system consists of pulse signal detection, respiration signal detection, electrocardiograph detection, A/D conversion and computer system parts. We define a pulse rate by a pulse count to the respiration period inspiration pulse rate by a pulse count to the inspiration period, and expiration pulse rate by a pulse count to the expiration period. The clinical experiments for normal Person to evaluate the pulse rate detection system show the pulse/respiration ratio of 4.30${\pm}$1.03, the pulse/inspiration ratio of 1.60${\pm}$0.32, the pulse/expiration ratio of 2.37${\pm}$0.75.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.198-206
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• 2019

A new methodology to analyze the nuclear material accountability for pyroprocessing system is developed. The $Pu-to-^{244}Cm$ ratio quantification is one of the methods for Pu accountancy in pyroprocessing. However, an uncertainty in the $Pu-to-^{244}Cm$ ratio due to the non-uniform composition in used fuel assemblies can affect the accountancy of Pu. A random variable, LOPu, is developed to analyze the probability of detection for Pu diversion of hypothetical scenarios at a pyroprocessing facility considering the uncertainty in $Pu-to-^{244}Cm$ ratio estimation. The analysis is carried out by the hypothesis testing and the event tree method. The probability of detection for diversion of 8 kg Pu is found to be less than 95% if a large size granule consisting of small size particles gets sampled for measurements. To increase the probability of detection more than 95%, first, a new Material Balance Area (MBA) structure consisting of more number of Key Measurement Points (KMPs) is designed. This multiple KMP-measurement for the MBA shows the probability of detection for 8 kg Pu diversion is greater than 96%. Increasing the granule sample number from one to ten also shows the probability of detection is greater than 95% in the most ranges for granule and powder sizes.

• Journal of Information Technology Applications and Management
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• v.12 no.1
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• pp.231-239
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• 2005

This paper describes a new algorithm for pixel-based skin color detection to differentiate human form in color images by the ratio of R to H. In order to detect skin color efficiently, we examine the distribution of the R, G and B color elements combining to constitute the skin color in various color images. It shows that R is located in a narrower area than G and B on the RGB color space. And skin color is more related to R than G and B. Meanwhile, when the color image is transformed to the HSI color space, the S is variously changed in accordance with skin colors. The I is changed in accordance with the quantity and angle of light. But the H is less influenced by other conditions except for color. On the basis of the aforementioned study, we propose that the threshold for skin color detection is decided by the ratio of R to H. The proposed method narrows down the range of threshold, detects more skin color and reduces mis-detection of skin color in comparison to detection by R or H. In experimentation. it shows that the proposed algorithm overcomes changes of brightness and color to detect skin color in color images.