• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2113-2128
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• 2019

Image thresholding techniques introducing spatial information are widely used image segmentation. Some methods are used to calculate the optimal threshold by building a specific histogram with different parameters, such as gray value of pixel, average gray value and gradient-magnitude, etc. However, these methods still have some limitations. In this paper, an entropic thresholding method based on Gabor histogram (a new 2D histogram constructed by using Gabor filter) is applied to image segmentation, which can distinguish foreground/background, edge and noise of image effectively. Comparing with some methods, including 2D-KSW, GLSC-KSW, 2D-D-KSW and GLGM-KSW, the proposed method, tested on 10 realistic images for segmentation, presents a higher effectiveness and robustness.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.169-180
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• 2019

Transmitting visual information over a broadcasting network is not only prone to a copyright violation but also is a forgery. Authenticating such information and protecting its authorship rights call for more advanced data encoding. To this end, electronic watermarking is often adopted to embed inscriptive signature in imaging data. Most existing watermarking methods while focusing on robustness against degradation remain lacking of measurement against security loophole in which the encrypting scheme once discovered may be recreated by an unauthorized party. This could reveal the underlying signature which may potentially be replaced or forged. This paper therefore proposes a novel digital watermarking scheme in temporal-frequency domain. Unlike other typical wavelet based watermarking, the proposed scheme employed the Lorenz chaotic map to specify embedding positions. Effectively making this is not only a formidable method to decrypt but also a stronger will against deterministic attacks. Simulation report herein highlights its strength to withstand spatial and frequent adulterations, e.g., lossy compression, filtering, zooming and noise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1538-1552
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• 2021

Machine learning models are vulnerable to adversarial examples generated by adding a deliberately designed perturbation to a benign sample. Particularly, for automatic speech recognition (ASR) system, a benign audio which sounds normal could be decoded as a harmful command due to potential adversarial attacks. In this paper, we focus on the countermeasures against audio adversarial examples. By analyzing the characteristics of ASR systems, we find that frame offsets with silence clip appended at the beginning of an audio can degenerate adversarial perturbations to normal noise. For various scenarios, we exploit frame offsets by different strategies such as defending, detecting and hybrid strategy. Compared with the previous methods, our proposed method can defense audio adversarial example in a simpler, more generic and efficient way. Evaluated on three state-of-the-arts adversarial attacks against different ASR systems respectively, the experimental results demonstrate that the proposed method can effectively improve the robustness of ASR systems.

• Journal of Sensor Science and Technology
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• v.32 no.1
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• pp.22-30
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• 2023

Innovative and advanced technologies, including robots, augmented reality, virtual reality, the Internet of Things, and wearable medical equipment, have largely emerged as a result of the rapid evolution of modern society. For these applications, pressure monitoring is essential and pressure sensors have attracted considerable interest. To improve the sensor performance, several new designs of pressure sensors have been researched based on resistive, capacitive, piezoelectric, optical, and triboelectric types. In particular, optical pressure sensors have been actively studied owing to their advantages, such as robustness to noise and remote sensing capability. Herein, a review of recent research on optical pressure sensors with self-powered sensing, remote sensing, high spatial resolution, and multimodal sensing capabilities is presented from the viewpoints of design, fabrication, and signal processing.

• Annual Conference of KIPS
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• 2011.11a
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• pp.1166-1169
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• 2011

In this paper, we design a Circle dot Code, In our scheme, we design a dot patterns for increasing maximum capacity and also for increasing robustness to Affine Transformation. Our code Can be extended according number of data circle. We use three data circle vision code. In this type code, after acquiring camera images for the Circle dot Codes, and perform error correction decoding using four position symbols and six CRC symbols. We perform graph based dot code analysis which determines the topological distance between dot pixels. Our code can be bridged the real world and ubiquitous computing environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.887-895
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• 2014

Drowsy driving is a large proportion of the total car accidents. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. Many researches have been published that to measure electroencephalogram(EEG) signals is the effective way in order to be aware of fatigue and drowsiness of drivers. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, transition, and drowsiness. This paper proposes a drowsiness detection system using errors-in-variables(EIV) for extraction of feature vectors and multilayer perceptron (MLP) for classification. The proposed method evaluates robustness for noise and compares to the previous one using linear predictive coding (LPC) combined with MLP. From evaluation results, we conclude that the proposed scheme outperforms the previous one in the low signal-to-noise ratio regime.

• Journal of KSNVE
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• v.9 no.4
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• pp.849-855
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• 1999

Neural Networks have shown potential to become an attractive alternative to classic methods for identification and control of non-linear dynamic systems. The purpose of this paper is to present an application of neural networks, that is a neural reconstruction of the input signal of a non-linear unknown system. This basic methodology could be used for practical purpose in several engineering fields. Clearly applications of the proposed scheme can be of interest for physical systems where a complete network of sensors measuring system inputs is not available. It should also be emphasized that the application of the reconstruction scheme is of little or no interest when the analyzed system works and operates at nominal conditions. In fact, only when failures and/or system anomailes occur, leasing to performance degradation and/or shutdown, the application of this scheme is of interest. The paper presents the results of the methodology applied to unknown non-linear dynamic systems and the robustness of the scheme to white and colored system noise was evaluated.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.120-123
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• 2003

In this paper, a digital watermarking scheme whichis effective in protecting a copyright of video image under an image transformation and impulse noise is proposed. The proposing scheme is to use a coded watermark that insert the personal ID of copyrighter. The recovery ability is improved by the coded watermark. Also the coded watermark is abel to trace the illegal distributors. Binary image is used as watermark image, the value of PSNR and recovered rates of watermark are obtained in order to confirm the required invisibility and robustness in watermark system. The experimental results show that image quality is less degraded as the PSNR of 98.21 ㏈. It is also observed that excellent watermark recovery is achieved under the image transformation and impulse noise.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.56-62
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• 2001

In this paper, we adopt a missing data theory to speech recognition. It can be used in order to maintain high performance of speech recognizer when the missing data occurs. In general, hidden Markov model (HMM) is used as a stochastic classifier for speech recognition task. Acoustic events are represented by continuous probability density function in continuous density HMM(CDHMM). The missing data theory has an advantage that can be easily applicable to this CDHMM. A marginalization method is used for processing missing data because it has small complexity and is easy to apply to automatic speech recognition (ASR). Also, a spectral subtraction is used for detecting missing data. If the difference between the energy of speech and that of background noise is below given threshold value, we determine that missing has occurred. We propose a new method that examines the reliability of detected missing data using voicing probability. The voicing probability is used to find voiced frames. It is used to process the missing data in voiced region that has more redundant information than consonants. The experimental results showed that our method improves performance than baseline system that uses spectral subtraction method only. In 452 words isolated word recognition experiment, the proposed method using the voicing probability reduced the average word error rate by 12％ in a typical noise situation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2A
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• pp.1-11
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• 2005

S-CDMA is the advanced physical layer modulation techniques of DOCSIS 2.0 specification. S-DMT is another challenging modulation technique for cable modem upstream channel due to the intrinsic robustness for fading and impulse noise. The BER performance of S-DMT and S-CDMA over the mixed channel model of AWGN and impulse noise were evaluated in comparison with TDMA. The mathematical BER derivation and the comparison of those three types of technique were performed based on the ${\varepsilon}-mixture$ non-Gaussian impulse noise model. The results of simulation show good compliance with those of analytic BER derivation. By the results of comparisons, it was verified that the performance of S-CDMA and S-DMT is almost the same, but the performance of S-DMT is far superior to that of TDMA at typical BER range of the practical data communications.