• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.361-373
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• 2002

In this paper, we propose a channel normalization method to improve the performance of CMS (cepstral mean subtraction) which is widely adopted to normalize a channel variation for speech and speaker recognition. CMS which estimates the channel effects by averaging long-term cepstrum has a weak point that the estimated channel is biased by the formants of voiced speech which include a useful speech information. The proposed Formant-broadened Cepstral Mean Subtraction (FBCMS) is based on the facts that the formants can be found easily in log spectrum which is transformed from the cepstrum by fourier transform and the formants correspond to the dominant poles of all-pole model which is usually modeled vocal tract. The FBCMS evaluates only poles to be broadened from the log spectrum without polynomial factorization and makes a formant-broadened cepstrum by broadening the bandwidths of formant poles. We can estimate the channel cepstrum effectively by averaging formant-broadened cepstral coefficients. We performed the experiments to compare FBCMS with CMS, PFCMS using 4 simulated telephone channels. In the experiment of channel estimation, we evaluated the distance cepstrum of real channel from the cepstrum of estimated channel and found that we were able to get the mean cepstrum closer to the channel cepstrum due to an softening the bias of mean cepstrum to speech. In the experiment of text-independent speaker identification, we showed the result that the proposed method was superior than the conventional CMS and comparable to the pole-filtered CMS. Consequently, we showed the proposed method was efficiently able to normalize the channel variation based on the conventional CMS.

• Geophysics and Geophysical Exploration
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• v.5 no.4
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• pp.299-308
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• 2002

We have derived an analytical expression for the sensitivity of the frequency domain small-loop electromagnetic (EM) surveys over a two-layer earth in order to estimate the depth of investigation with an instrument having the source-receiver separation of about 2 m. We analyzed the sensitivities to the lower layer normalized by those to the upper half-space and estimated the depth of investigation from the sensitivity analyses and the mutual impedance ratio. The computational results showed that the in-phase components of the sensitivity to the lower layer dominates those to the upper layer when the thickness of the upper layer is less than 20 m, while the quadrature components are not sensitive to the lower layer over the entire frequency range. Hence we confirmed that the accurate measurement of the in-phase component is essential to increase the depth of investigation in the multi-frequency small-loop EM survey. When conductive basement of 10 ohm-m underlies the upper layer of 100 ohm-m, an accurate measurement of the in-phase components ensures the depth of the investigation more than 10 m even accounting a noise effect, from which we conclude that the small-loop EM survey is quite effective in imaging the conductive plume down to a considerable depth. On the other hand, in the presence of the resistive basement of 1,000 ohm-m, the depth of investigation may not exceed 5 m considering the instrumental accuracy, which implies that the application of the small-loop EM survey is not recommended over the resistive environment other than detecting the buried conductor.

• Journal of the Korea Computer Graphics Society
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• v.9 no.3
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• pp.23-29
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• 2003

There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of the previous block. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous frame, the total number of search points used to find the motion vector of the current block may be reduced significantly. In this paper, we propose the block-matching motion estimation using an adaptive initial search point by the predicted motion information from the same block of the previous frame. And the first search point of the proposed algorithm is moved an initial point on the location of being possibility and the searching process after moving the first search point is processed according to the fast search pattern. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved UP to the 1.05dB as depend on the image sequences and improved about 0.33~0.37dB on an average. Search times are reduced about 29~97% than the other fast search algorithms. Simulation results also show that the performance of the proposed scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS(Full Search) algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.103-112
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• 2010

In this paper, we propose a coarse and fine frequency synchronization method which is suitable for the 3GPP(3rd Generation Partnership Project) LTE(Long Term Evolution) FDD(Frequency Division Duplexing) / TDD(Time Division Duplexing) dual mode system. In general, PSS(Primary Synchronization Signal) correlation based estimation method and CP(Cyclic Prefix) correlation based tracking loop are applied for coarse and fine frequency synchronization in 3GPP LTE OFDMA(Orthogonal Frequency Division Multiple Access) system, respectively. However, the conventional coarse frequency synchronization method has performance degradation caused by fading channel and squaring loss. Also, the conventional fine frequency synchronization method cannot guarantee stable operation in TDD mode because of signal power difference between uplink and downlink subframe. Therefore, in this paper, we propose enhanced coarse and fine frequency synchronization methods which can estimate more accurately in multi-path fading channel and high speed channel environments and has stable operation for TDD frame structure, respectively. By computer simulation, we show that the proposed methods outperform the conventional methods, and verify that the proposed frequency synchronization method can guarantee stable operation in 3GPP LTE FDD/TDD dual mode downlink receiver.

• Journal of KIISE
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• v.42 no.5
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• pp.642-651
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• 2015

A vanishing point is a point where parallel lines converge, and they become evident when a camera's lenses are used to project 3D space onto a 2D image plane. Vanishing point detection is the use of the information contained within an image to detect the vanishing point, and can be utilized to infer the relative distance between certain points in the image or for understanding the geometry of a 3D scene. Since parallel lines generally exist for the artificial structures within images, line-detection-based vanishing point-detection techniques aim to find the point where the parallel lines of artificial structures converge. To detect parallel lines in an image, we detect edge pixels through edge detection and then find the lines by using the Hough transform. However, the various textures and noise in an image can hamper the line-detection process so that not all of the lines converging toward the vanishing point are obvious. To overcome this difficulty, it is necessary to assign a different weight to each line according to the degree of possibility that the line passes through the vanishing point. While previous research studies assigned equal weight or adopted a simple weighting calculation, in this paper, we are proposing a new method of assigning weights to lines after noticing that the lines that pass through vanishing points typically belong to artificial structures. Experimental results show that our proposed method reduces the vanishing point-estimation error rate by 65% when compared to existing methods.

• International Journal of Highway Engineering
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• v.12 no.3
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• pp.87-92
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• 2010

As the Concept "how environmental friendly" becomes more and more important in road construction. However, so far there is no estimation method. Environmental friendly concept can be incorporated at the plan level in order to influence decision making, and support policies that affect environment. The overall goal of this study was to develop environmental friendly concept measures for the national highway and to develop a methodology to implement a more environmental friendly concept. The research identified 8 performance measures through a project analysis that could address environmental impact assessment system's ten strategic goals - Topography, Wildlife, hydrology, landuse, air quality, water quality, soil, waste, noise, landscape. The qualitatively and quantitatively evaluation approach was selected as the decision support framework and performance measure were investigated using the AHP(Analytic Hierarchy Process) and pilot corridor for a 10 section and calculate the index values. The methodology was applied to a pilot corridor comprised of a 120km section of national highway in korea. The methodology made it possible to identify the specific performance measures that need improvement to enhance the overall environmental friendly concept. It is fairly intuitive, based on readily available data, and is easy to apply. It provides a powerful tool for government to assess the relative environmental friendly conceptof their transportation corridors now and in the future. It allows for comparisons within a corridor and with other corridors and identifies the improvements needed to enhance the environmental friendly concept.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.325-342
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• 1998

Two RADARSAT SAR images with different modes acquired by Canadian Space Agency to test the effectiveness of geological lineament extraction and spring water detection over the Cheju Island. Geological lineaments are poorly developed this basalt dominant volcanic island, but more linear features can be extracted when SAR and TM images are simultaneously analyzed than when TM image alone is used. This results mainly owe to the facts that RADARSAT SAR systems are able to provide data with different frequencies, azimuth, and incidence angles. Distribution of spring water along coast is poorly correlated with geological lineaments or drainage pattern, but those in middle range of mountain region are developed along geological lineaments. Detection of spring water using remotely sensed images are turned out to be very difficult to achieve. Radial shaped sea surface temperature anomaly derived from TM thermal band should be the best candidate for spring water, but the resolution is not high enough. We also investigate the normalized radar cross section (or sigma naught) converted from RADARSAT and ERS-1 SAR data but to discriminate the spring water effectively except where relatively large water mass is observed on land side. Speckle noise and irregularity in physical sea surface condition are the serious obstacles for this application. ERS-1 SAR image acquired in low incidence angle was more useful for geological lineament estimation and water body study than RADARSAT SAR images with high incidence angles. Therefore the selection of incidence angle is critical in geological and spring water applications of SAR images, and low incidence angles less than about 30$^{\circ}$ are recommended to monitor the Cheju volcanic island.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.320-329
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• 2021

In this paper, an empirical model of air bubble size to be applied to an air masker for reduction of underwater radiation noise is presented. The proposed model improves the divergence problem under the low-speed flow condition of the existing model derived using Rayleigh's jet instability model and simple continuity condition by introducing a jet flow velocity of air. The jet flow velocity of air is estimated using the bubble size where the liquid is quiescent. In a medium without flow, the size of the bubble is estimated by an empirical method where bubble formation regime is divided into a laminar-flow range, a transition range, and a turbulent-flow range based on the Reynolds number of the injected air. The proposed bubble size model is confirmed to be in good agreement with the Computational Fluid Dynamics (CFD) analysis result and the experimental results of the existing literature. Using the acoustic inversion method, the air bubble population is estimated from the insertion loss measured during the air injection experiment of the air- masker model in a large cavitation tunnel. The results of the experiments and the bubble size model are compared in the paper.

• Journal of Navigation and Port Research
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• v.43 no.3
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• pp.172-178
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• 2019

Although the needs for providing resilient PNT information are increasing, threats due to the intentional RFI or space weather change are challenging to resolve. eLoran, which is a terrestrial navigation system that use a high-power signal is considered as a best back-up navigation system. Depending on the user's environment in the eLoran system, the user may use one of E-field or H-field antennas. H-field antenna, which has no restriction on setting stable ground and is relatively resistant to noise of general electronic equipment, is composed of two loops, and shows anisotropic gain pattern due to the different measurement at the two loops. Therefore, the H-field antenna's phase estimation value of signal varies depending on its direction even at the static environment. The error due to the direction of the signal should be eliminated if the user want to estimate the own position more precisely. In this paper, a method to compensate the error according to the geometric distribution between the H-field antenna and the transmitting station is proposed. A model was developed to compensate the directional error of H-field antenna based on the signal generated from the eLoran signal simulator. The model is then used to the survey measurement performed in the land area and verify its performance.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.457-464
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• 2021

The advent of the big data era has enabled the rapid development of deep learning that learns rules by itself from data. In particular, the performance of CNN algorithms has reached the level of self-adjusting the source data itself. However, the existing image processing method only deals with the image data itself, and does not sufficiently consider the heterogeneous environment in which the image is generated. Images generated in a heterogeneous environment may have the same information, but their features may be expressed differently depending on the photographing environment. This means that not only the different environmental information of each image but also the same information are represented by different features, which may degrade the performance of the image analysis model. Therefore, in this paper, we propose a method to improve the performance of the image color constancy model based on Adversarial Learning that uses image data generated in a heterogeneous environment simultaneously. Specifically, the proposed methodology operates with the interaction of the 'Domain Discriminator' that predicts the environment in which the image was taken and the 'Illumination Estimator' that predicts the lighting value. As a result of conducting an experiment on 7,022 images taken in heterogeneous environments to evaluate the performance of the proposed methodology, the proposed methodology showed superior performance in terms of Angular Error compared to the existing methods.