• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.252-253
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• 2023

Container terminal automation might offer many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A robust lane detection method is proposed using score-based generative modeling through stochastic differential equations for image-to-image translation. Image processing techniques are combined with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithm (GA) to ensure lane positioning robustness. The proposed method is validated by a dataset collected from the port terminals under different environmental conditions and tested the robustness of the lane detection method with stochastic noise.

• Journal of Sensor Science and Technology
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• v.23 no.1
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• pp.1-6
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• 2014

In many medical image devices, dc noise often prevents normal diagnosis. In wireless capsule endoscopy systems, multipath fading through indoor wireless links induces inter-symbol interference (ISI) and indoor electric devices generate impulsive noise in the received signal. Moreover, dc noise, ISI, and impulsive noise are also found in optical fiber communication that can be used in remote medical diagnosis. In this paper, a blind signal processing method based on the biased probability density functions of constant modulus error that is robust to those problems that can cause error propagation in decision feedback (DF) methods is presented. Based on this property of robustness to error propagation, a DF version of the method is proposed. In the simulation for the impulse response of optical fiber channels having slowly varying dc noise and impulsive noise, the proposed DF method yields a performance enhancement of approximately 10 dB in mean squared error over its linear counterpart.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1946-1963
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• 2014

Most background subtraction methods focus on dynamic and complex scenes without considering robustness against noise. This paper proposes a background subtraction algorithm based on dictionary learning and sparse coding for handling low light conditions. The proposed method formulates background modeling as the linear and sparse combination of atoms in the dictionary. The background subtraction is considered as the difference between sparse representations of the current frame and the background model. Assuming that the projection of the noise over the dictionary is irregular and random guarantees the adaptability of the approach in large noisy scenes. Experimental results divided in simulated large noise and realistic low light conditions show the promising robustness of the proposed approach compared with other competing methods.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.784-786
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• 1993

Recently, in the industrial applications, the sensorless system is developed, but the sensorless system is required to have robustness for the measurement noise and disturbance. In this paper, for the sensorless system, the method of designing a robust sliding mode observer taking account of the ability of disturbance and noise attenuation is presented. Also, the strategy for the estimation of rotor flux using the sliding mode observer, which is robust to the measurement noise, is described. Robustness are achieved by assigning the pole of the the system during the sliding motion in such a way as to minimize the effects of the disturbances on the rotor flux estimation error. Finally, using worst case desist and LQC(least square error design), the sliding mode absolver is verified by computer simulations.

• Journal of Digital Contents Society
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• v.5 no.1
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• pp.87-94
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• 2004

In this paper, the digital watermarking algorithm is proposed using CDMA technique for protection of the mobile contents in the mobile environment. The digital watermarking was designed to robust the errors in the mobile environment where pathloss, multipath fading, interference, and noise exist. In case of the multimedia content service in the mobile environment, the construction method of the watermark, the algorithm of insertion and detection are also proposed. The watermark consists of the information of the mobile user. Invisibility and robustness required in watermarking are etimated. It is observed that PSNR of the mobile content inserted the watermark is 90.31 dB, and the signal processing and noise attack are also robust. Especially, because random noise occurs in wireless transmission can overcome, the proposed watermarking algorithm is adequate for protection of the multimedia contents in the mobile environment.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.3
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• pp.264-271
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• 2021

Raman spectroscopy is an equipment that is widely used for classifying chemicals in chemical defense operations. However, the classification performance of Raman spectrum may deteriorate due to dark current noise, background noise, spectral shift by vibration of equipment, spectral shift by pressure change, etc. In this paper, we compare the classification accuracy of various machine learning algorithms including k-nearest neighbor, decision tree, linear discriminant analysis, linear support vector machine, nonlinear support vector machine, and convolutional neural network under noisy and spectral shifted conditions. Experimental results show that convolutional neural network maintains a high classification accuracy of over 95 % despite noise and spectral shift. This implies that convolutional neural network can be an ideal classification algorithm in a real combat situation where there is a lot of noise and spectral shift.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3E
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• pp.3-8
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• 1999

In speech recognition for real-world applications, the performance degradation due to the mismatch introduced between training and testing environments should be overcome. In this paper, to reduce this mismatch, we provide a hybrid method of spectral subtraction and residual noise masking. We also employ multiple model approach to obtain improved robustness over various noise environments. In this approach, multiple model sets are made according to several noise masking levels and then a model set appropriate for the estimated noise level is selected automatically in recognition phase. According to speaker independent isolated word recognition experiments in car noise environments, the proposed method using model sets with only two masking levels reduced average word error rate by 60% in comparison with spectral subtraction method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.9
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• pp.663-669
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• 2004

The mobile tole-cardiology system is the new research area that support an ubiquitous health care based on mobile telecommunication networks. Although there are many researches presenting the modeling concepts of a GSM-based mobile telemedical system, practical application needs to be considered both compression performance and error corruption in the mobile environment. This paper evaluates three wavelet ECG compression algorithms over CDMA networks. The three selected methods are Rajoub using EPE thresholding, Embedded Zerotree Wavelet(EZW) and Wavelet transform Higher Order Statistics Coding(WHOSC) with linear prediction. All methodologies protected more significant information using Forward Error Correction coding and measured not only compression performance in noise-free but also error robustness and delay profile in CDMA environment. In addition, from the field test we analyzed the PRD for movement speed and the features of CDMA 1X. The test results show that Rajoub has low robustness over high error attack and EZW contributes to more efficient exploitation in variable bandwidth and high error. WHOSC has high robustness in overall BER but loses performance about particular abnormal ECG.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.85-90
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• 2019

This paper related with the M-CMA adaptive equalization algorithm which is possible to improve the residual isi and robustness performance compare to the current MMA algorithm that is reduce the intersymbol interference occurs in channel when transmitting the QAM signal. The current MMA algorithm depend on the cost function and error function using fixed signal dispersion constant, but the M-CMA algorithm depend on the new proposed cost function and error function using multiple dispersion constant. By this, it is possible to having robustness of the CMA and simultaneous compensation of amplitude and phase of MMA. The computer simulation was performed in the same channel and noise environment for compare the proposed M-CMA and current MMA algorithm. The equalizer output signal constellation, residual isi, MD, MSE learning courves and SER, represents the robustness were used for performance index. As a result of simulation, the M-CMA has more superior to the MMA in robustness and other performance index.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.220-222
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• 2008