• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.249-252
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• 1993

In speech signal processing, The accurate detection of the voiced/unvoiced is important for robust word recognition and analysis. This algorithm is based on the MD in the frame of speech signals that does not require statistical information about either signal or background-noise to decide a voiced/unvoiced. This paper presents a method of estimation the Characteristic of Magnitude Distribution from noisy speech and also of estimation the optimal threshold based on the MD of the voiced/unvoiced decision. The performances of this detectors is evaluated and compared to that obtained from classifying other paper.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.194-195
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• 2019

In this paper, we propose a frequency location adaptive hard-decision quantization (HDQ) scheme for video coding. A threshold for zero quantized level is adaptively applied to unquantized transform coefficients based on its frequency location in the transform domain. The proposed method achieves an average of 1.13%, 1.57%, and 1.53% of bit-rate reduction in BDBR sense compared to the conventional HDQ scheme respectively in Y, Cb, and Cr under the all intra encoding configuration.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.84-90
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• 2010

In this paper, we propose a quadratic discriminant analysis based approach for improving the discriminating strength of weak classifiers based on simple Haar-like features that were used in the Viola-Jones object detection framework. Viola and Jones built a strong classifier using a boosted ensemble of weak classifiers. However, their single threshold (or decision boundary) based weak classifier is sub-optimal and too weak for efficient discrimination between object class and background. A quadratic discriminant analysis based approach is presented which leads to hyper-quadric boundary between the object class and background class, thus realizing multiple thresholds based weak classifiers. Experiments carried out for car detection using 1000 positive and 3000 negative images for training, and 500 positive and 500 negative images for testing show that our method yields higher classification performance with fewer classifiers than single threshold based weak classifiers.

• International Journal of Highway Engineering
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• v.16 no.3
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• pp.85-99
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• 2014

PURPOSES : This study has been performed with the objective to determine threshold zone luminance of adaptation luminance by target safety level in a vehicular traffic tunnel with design speed set at 100km/h. METHODS : The study made a miniature capable of portraying changes in luminance distribution within $2{\times}10^{\circ}$ conical field of view of the driver approaching to the tunnel for the test. Test conditions were set based on justifications for CIE 88-1990's threshold zone luminance used as a reference by domestic tunnel light standards (KS C 3703 : 2010). Luminance contrast of object background and object is 23%, object presentation duration is 0.5 seconds, and size of the object background is $7.3{\times}11.5m^2$ RESULTS : Threshold zone luminance was set within adaptation luminance of $100{\sim}3,000cd/m^2$. Adaptation luminance and threshold zone luminance based on 50%, 75% and 90% target safety level all showed a relatively high linear relationship. According to findings in the study, it is not appropriate to specify the relationship between adaptation luminance and threshold zone luminance as luminance ratio. Rather, direct utilization of the linear relationship gained from the study findings appears to be the better solution. CONCLUSIONS : Findings of this study may be used to determine operation of threshold zone luminance based on target safety level. However, a proper verification and validity of test results are required. Furthermore, a study to determine proper threshold zone luminance level considering target safety level reviewed in this study and various decision-making factors such as economic conditions in Korea and energy-related policies should be carried out in addition. Additional tests on adaptation luminance greater than $3,000cd/m^2$ will be performed, through which application scope of the test findings will be broadened.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1161-1168
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• 2003

In this paper, we propose an improved statistical model-based voice activity detection algorithm and threshold update method. We first improve signal-to-noise ratio by using speech enhancement preprocessing algorithm combined power subtraction method and matched filter, then apply it to LLR test optimum decision rule for improving the performance even in low SNR conditions. And we propose an adaptive threshold update method that was not concerned in any papers. We also perform extensive computer simulations to demonstrate the performance improvement of the proposed VAD algorithm employing the proposed speech enhancement preprocessing algorithm and adaptive threshold update method under various background noise environments. Finally we verify our results by comparing ITU-T G.729 Annex B.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1660-1668
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• 2004

This paper proposes a Voice Activity Detection (VAD) algorithm based on Radial Basis Function (RBF) network using dual threshold. The k-means clustering and Least Mean Square (LMS) algorithm are used to upade the RBF network to the underlying speech condition. The inputs for RBF are the three parameters in a Code Exited Linear Prediction (CELP) coder, which works stably under various background noise levels. Dual hangover threshold applies in BRF-VAD for reducing error, because threshold value has trade off effect in VAD decision. The experimental result show that the proposed VAD algorithm achieves better performance than G.729 Annex B at any noise level.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.2
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• pp.175-181
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• 2014

In this paper, we propose a robust clutter pre-thresholding method using background adaptive Threshold Map for the clutter rejection in the complex coastal environment. The proposed algorithm is composed of the use of Threshold Map's and method of its calculation. Additionally we also suggest an automatic decision method of Thresold Map's update. Experimental results on some sets of real infrared image sequence show that the proposed method could remove clutters effectively without any loss of detection rate for the aim target and reduce processing time dramatically.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.4
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• pp.82-87
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• 1999

The Asynchronous Transfer Mode(ATM) networks are being adopted as backbones over various parts of Internet. TCP is one of the most widespread transport protocols and can be used with ATM. But, TCP shows poor end-to-end performance on ATM networks. Effective throughput of TCP over ATM can be quite low when cells are dropped at the congested ATM switch. As congested link transmits cells from corrupted packets, it wastes bandwidth and throughput becomes low. This paper examines the behavior of TCP over ATM-UBR using EPD switch in a broadband environment. As threshold value closes to the buffer size, the buffer can be used more efficiently, but more drops and retransmission occur. If the threshold value is much less than buffer size, efficiency becomes low, but few drops can be happen. Therefore, the decision of threshold value becomes important factor.

• Current Optics and Photonics
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• v.8 no.3
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• pp.239-245
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• 2024

This paper proposes single logarithmic amplification (single-LA) and deep learning (DL)-based fixed-threshold on-off keying (OOK) detection for free-space optical (FSO) communication. Multilevel LAs (MLAs) can be used to mitigate intensity fluctuations in the received OOK signal by their nonlinear gain characteristics; however, it is ineffective in the case of high scintillation, owing to degradation of the OOK signal's extinction ratio. Therefore, a DL technique is applied to realize effective scintillation compensation in single-LA applications. Fully connected (FC) networks and fully connected neural networks (FCNN), which have nonlinear modeling characteristics, are deployed in this work. The performance of the proposed method is evaluated through simulations under various scintillation effects. Simulation results show that the proposed method outperforms the conventional adaptive-threshold-decision, single-LA-based, MLA-based, FC-based, and FCNN-based OOK detection techniques.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.1
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• pp.23-28
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• 2013

The process of a feature matching for two different spatial data sets is similar to the process of classification as a binary class such as matching or non-matching. In this paper, we calculated a threshold by applying an equal error rate (EER) which is widely used in biometrics that classification is a main topic into spatial data sets. In a process of discriminating what's a matching or what's not, a precision and a recall is changed and a trade-off appears between these indexes because the number of matching pairs is changed when a threshold is changed progressively. This trade-off point is EER, that is, threshold. To the result of applying this method into training data, a threshold is estimated at 0.802 of a value of shape similarity. By applying the estimated threshold into test data, F-measure that is a evaluation index of matching method is highly value, 0.940. Therefore we confirmed that an accurate threshold is calculated by EER without person intervention and this is appropriate to matching different spatial data sets.