• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.2 s.17
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• pp.1-8
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• 2005

Microwave tomographic imaging technology using a bi-focusing operator has been developed in order to detect the internal voids/objects inside concrete structures. The imaging system consists of several cylindrical or planar array antennas for transmitting and receiving signals, and a numerical focusing operator is applied to the external signals both in transmitting and in receiving fields. In this study, the authors developed 3-dimensional (3D) electromagnetic (EM) imaging technology to detect such damage and to identify exact location of steel rebars or dowel. The authors have developed sub-surface two-dimensional (2D) imaging technique using tomographic antenna array in previous works. In this study, extending the earlier analytical and experimental works on 2D image reconstruction, a 3D microwave imaging system using tomographic antenna way was developed, and multi-frequency technique was applied to improve quality of the reconstructed image and to reduce background noises. Numerical simulation demonstrated that a sub-surface image can be successfully reconstructed by using the proposed tomographic imaging technology. For the experimental verification, a prototype antenna array was fabricated and tested on a concrete specimen.

• Geophysics and Geophysical Exploration
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• v.14 no.2
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• pp.140-145
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• 2011

In order to analyze the influence of the noise on a cross-well traveltime tomography to detect a small scale low velocity body in a homogeneous medium, the first arrival travel times were computed one a tunnel model by a finite-difference ray tracing scheme. Three different types and four different intensity levels of white noises were added to the computed first arrival travel times, and velocity tomograms were constructed using an iterative inversion method (SIRT). Tomograms with the noise intensity up to 10% of the maximum traveltime delay in the tunnel model, showed the exact location of the tunnel. However, the velocity shown at the tunnel location was not close to air velocity but only slightly less than the velocity of the background medium. The additive random noise showed significantly less degree of influence on the resulting tomogram than the source- and receiver consistent noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2019-2026
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• 2001

In this paper, we proposed the car license plate extraction and recognition algorithm using both the dynamical thresholding method and the kohonen algorithm. In general, the areas of car license plate in the car images have distinguishing characteristics, such as the differences in intensity between the areas of characters and the background of the plates, the fixed ratio of width to height of the plates, and the higher dynamical thresholded density rate 7han the other areas, etc. Taking advantage of the characteristics, the thresholded images were created from the original images, and also the density rates were computed. A candidate area was selected, whose density rate was corresponding to the properties of the car license plate obtained from the car license plate. The contour tracking method by utilizing the Kohonen algorithm was applied to extract the specific area which included characters and numbers from an extracted plate area. The characters and numbers of the license place were recognized by using Kohonen algorithm. Kohonen algorithm was very effective o? suppressing noises scattered around the contour. In this study, 80 car images were tested. The result indicate that we proposed is superior in performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.75-84
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• 2003

Current techniques for road-traffic monitoring rely on sensors which have limited capabilities, are costly and disruptive to install. The use of video cameras coupled with computer vision techniques offers an attractive alternative to current sensors. Video based traffic monitoring systems are now being considered key points of advanced traffic management systems. In this paper, we propose the new method which extract the traffic information using video camera. The proposed method uses an adaptive updating scheme for background in order to reduce the false alarm rate due to various noises in images. also, the proposed extraction method of traffic information calculates the traffic volume ratio of vehicles passing through predefined detection area, which is defined by the length of profile occupied by cars over that of overall detection area. Then the ratio is used to define 8 different states of traffic and to interpret the state of vehicle flows. The proposed method is verified by an experiment using CCTV traffic data from urban area.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.2
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• pp.332-338
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• 2010

Annually, electrical fires caused by arcing phenomena in power system rapidly increase as the use of more electric appliances, but there is no established method for the prevention of the accidents. With this background, this paper dealt with the experimental results on a series arc detection technique and a device for air conditioners. Series arcing phenomena that is generated in incomplete connection of air conditioners was simulated, and the frequency spectrum was analyzed. The Fast Fourier Transform (FFT) of the arc pulse showed that the dominant frequency components exist in ranges of 190 kHz~250 kHz and 900 kHz~1.6 MHz. An arc detection circuit with low cut off frequency of 170 kHz to attenuate 60 Hz by 170 dB and a signal discriminator were designed. Also, an algorithm which separate series arc signal from unwanted noises produced by switching operation, inverter, and surge was proposed. Application experiment was carried out on several types of air-conditioners by using the arc generator specified in UL1699, and the results showed the over 99 % accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.80-87
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• 2011

In this paper we present subject region-based auto-focusing algorithm using noise robust focus measure. The proposed algorithm automatically estimates the main subject using entropy and solves the traditional problems with a subject position or high frequency component of background image. We also propose a new focus measure by analyzing the discrete cosine transform coefficients. Experimental results show that the proposed method is more robust to Gaussian and impulse noises than the traditional methods. The proposed algorithm can be applied to Pan-tilt-zoom (PTZ) cameras in the intelligent video surveillance system.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.51 no.3
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• pp.340-347
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• 2015

The Commission for Conservation of Antarctic Marine Living Resources (CCAMLR) is utilized to manage krill resources using acoustic data collection and a scientific observer program operating on the fishing boats. However, the acoustic data were contained seriously noise, example of background, spike, and intermittent noise, due to purpose of fish boats. In this study, the noise removal techniques were confirmed the potential of the acoustic data analysis. Acoustic system and frequency used in the survey were commercial echosounder (ES70, SIMRAD) and 200 kHz split beam transducer. Acoustic data were analyzed using Echoview software (Myriax), and general data analysis and new noise removal method was used. Although a variety of noise, most of the noises have been removed using the noise removal processing. We confirmed the possibility of analyzing the acoustic data obtained from fish boats. The results will be useful for analysis of the acoustic data acquired from krill fishing boats.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.60-69
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• 2000

In this paper we propose a new two-color signal processing algorithm for efficient target tracking under complicated condition including interfernces such as background noises and countermeasures. For the efficient target tracking, we adopt two detection bands, and define the ratio between two band signals which represents the spectral distribution characteristics of a target or interference. The proposed algorithm detects the ratio of interference, and extracts only the target signal from the target and the interference mixed signal by using it. To evaluate the performance of the proposed algorithm, we apply it to a rosette tracker and perform various simulations. The simulation results show that the proposed algorithm extracts the target signal from the mixed signal well. The proposed algorithm is also ready to be applied to a real system since it is simple and adaptive for environment change.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.101-107
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• 2011

The background noises and distortions by channel are major factors that disturb the practical use of speech recognition. Usually, noise reduce the performance of speech recognition system DSR(Distributed Speech Recognition) based speech recognition also bas difficulty of improving performance for this reason. Therefore, to improve DSR-based speech recognition under noisy environment, this paper proposes a method which detects accurate speech region to extract accurate features. The proposed method distinguish speech and noise by using entropy and detection of spectral energy of speech. The speech detection by the spectral energy of speech shows good performance under relatively high SNR(SNR 15dB). But when the noise environment varies, the threshold between speech and noise also varies, and speech detection performance reduces under low SNR(SNR 0dB) environment. The proposed method uses the spectral entropy and harmonics of speech for better speech detection. Also, the performance of AFE is increased by precise speech detections. According to the result of experiment, the proposed method shows better recognition performance under noise environment.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.81-88
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• 2007

We implement automobile license plates recognition system. These days automobile license plate recognition systems are widely used for tracing stolen cars. managing parking facilities, ticketing speeding cars, and so on. Recognition systems largely consist of three parts plates extraction, segments extraction, and segment recognition. For plates extraction, we measure the degree of inclination of plate. We use filters that extract only the horizontal components of the front of an automobile to measure the degree of inclination. For segment extraction, we trace the change of the number of blocks that consist solely of foreground pixels or background pixels as the horizontal scanning line moves along upward. For recognition of each individual letter or digit, we devise a variant of template matching method, called comparative template matching. Through experiments, we show that comparative template matching is less prone misled by noises and exhibits higher performance compared to the traditional method of template matching or histogram based recognition.