• The Journal of the Acoustical Society of Korea
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• v.19 no.4
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• pp.16-22
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• 2000

In order to predict the performance and the usefulness of the narrow-band underwater acoustic measurement system at design stage, whose error variance is not clearly described, in this study a boundary equation to estimate the measurement accuracy is proposed based on the confidency as SNR variation. The boundary is presented as a function of SNR and the number of samples. In this paper, the measurement performance for narrow-band signal is simulated by the proposed boundary equation and the results are reviewed in the biased noise condition and separately in the background noise rejected condition.

• Journal of Astronomy and Space Sciences
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• v.29 no.2
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• pp.97-101
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• 2012

Monitoring sunspots consistently is the most basic step required to study various aspects of solar activity. To achieve this goal, the observers must regularly calculate their own correction factor $k$ and keep it stable. Relatively recently, two observing teams in South Korea have presented interesting papers which claim that revisions that take the yearly-basis $k$ into account lead to a better agreement with the international relative sunspot number $R_i$, and that yearly $k$ apparently varies with the solar cycle. In this paper, using artificial data sets we have modeled the sunspot numbers as a superposition of random noise and a slowly varying background function, and attempted to investigate whether the variation in the correction factor is coupled with the solar cycle. Regardless of the statistical distributions of the random noise, we have found the correction factor increases as sunspot numbers increase, as claimed in the reports mentioned above. The degree of dependence of correction factor $k$ on the sunspot number is subject to the signal-to-noise ratio. Therefore, we conclude that apparent dependence of the value of the correction factor $k$ on the phase of the solar cycle is not due to a physical property, but a statistical property of the data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.56-62
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• 2009

In this paper we investigate an analytical approach for noise properties and geometric structure in Computed Radiography(CR) images of industrial steel-tubes. Over thirty diverse radiographic images are sampled from industrial radiography measurements according to radiation intensity. Each image consists of three regions; background, thickness and inner-tube. Among these the region of inner-tube is selected for the object of analysis. Geometric structure which includes the noise generation is analyzed by the statistical and functional methodology. The analysis is carried on spacially and line by line. It verifies the geometrical transfigure from the circle configuration of steel-tube and noise variation. The estimation of fitting function and its error are the geometric factors. The statistics such as standard deviation, mean and signal-to-noise ratio are noise parameters for discrimination. These factors are considered under the intensity variation which is the penetrative strength of radiation. The analysing results show that the original geometry of circle is preserved in the form of elliptic or short/long diameter circle, and the noise deviation has increased inverse proportional to the radiation intensity.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.369-374
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• 2002

In this paper, we propose the react-time car license plate recognition algorithm using intensity variation and geometric pattern vector. Generally, difference of car license plate region between character and background is more noticeable than other regions. And also, car license plate region usually shows high density values as well as constant intensity variations. Based on these characteristics, we first extract car license plate region using intensity variations. Secondly, lightness compensation process is performed on the considerably dark and brightness input images to acquire constant extraction efficiency. In the proposed recognition step, we first pre-process noise reduction and thinning steps. And also, we use geometric pattern vector to extract features which independent on the size, translation, and rotation of input values. In the experimental results, the proposed method shows better computation times than conventional circular pattern vector and better extraction results regardless of irregular environment lighting conditions as well as noise, size, and location of plate.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.11
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• pp.52-62
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• 1995

We developed a two-dimensional numerical simulator which can analyze the electrical as well as optical characteristics and evaluate the detection performances of self-signal processing infrared detectors. It solves the poisson equation and the electron, hole current continuity equations including the optical generation and recombination models. To speed up convergency rate. the Newton algorithm is used. Automatic triangular grid generator make it easy to simulate the devices with the various read-out geometries. This simulator can show the variation of spatial resolution which is caused by the transit velocity and transit time dispersion in bifurcate and horn geometries respectively. Also, we calculated the responsivity, noise, and detectivity in respect of the applied electric field and background field-of-view. The results obtained from simulation correspond to those of experiments, and it is verified that horn read-out geometry has the superior spatial resolution and detection performance to bifurcate geometry.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.5
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• pp.385-393
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• 2001

We have developed a Differential Absortion LIDAR (DIAL) method for the measurement of lower tropospheric ozone concentration. We used two laser beams from quadrupled Nd:YAG (266 nm) for the resonance wavelength and dye lasers (299.5 nm) for non -resonance wavelength. Aerosol extinction coefficients in the lower troposphere was computed by both Klett and Slope methods. To correct the SIN (Signal -Induced Noise) effect caused by photo detector, we subtracted a new-fitted baseline on the background part of a LIDAR signal, after the subtraction of the DC level. This is because SIN can be treated as an exponentially decaying tail. Using theme results, ozone profiles were obtained approximately 2km at daytime and 3km at nighttime. We compared the results derided by the Slope method with those measured by UV spectrometer. The computed results are in mostly good agreement with experimental results. In the measurement of the vertical layer, we observed the variation of the ozone profiles around the top mixed layer.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.10
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• pp.120-129
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• 1996

This paper presents an efficient block segmentation and classification using the edge information of the document image. We extract four prominent features form the edge gradient and orientaton, all of which, and thereby the block clssifications, are insensitive to the background noise and the brightness variation of of the image. Using these four features, we can efficiently classify a document image into the seven categrories of blocks of small-size letters, large-size letters, tables, equations, flow-charts, graphs, and photographs, the first five of which are text blocks which are character-recognizable, and the last two are non-character blocks. By introducing the clumn interval and text line intervals of the document in the determination of th erun length of CRLA (constrained run length algorithm), we can obtain an efficient block segmentation with reduced memory size. The simulation results show that the proposed algorithm can rigidly segment and classify the blocks of the documents into the above mentioned seven categories and classification performance is high enough for all the categories except for the graphs with too much variations.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.105-107
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• 2004

In this work, we suggested the method which improves the efficiency of the face detection algorithm using Pulse-Coupled Neural Network. Face detection algorithm which uses the color information is independent on size, angle, and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise, and so on. Depending on these conditions, we obtained the mean and variance of skin-tone colors by experiments. Then we introduce a preprocess that the pixel with a mean value of skin-tone colors has highest level value(255) and the other pixels in the skin-tone region have values between 0 and 255 according to a normal distribution with a variance. This preprocess leads to an easy decision of the linking parameters.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1718-1727
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• 2009

Traditional character recognition systems usually aim at characters with simple variation. With the development of multimedia technology, printed characters may appear more diversely. Existing recognition technologies can't deal with Hangul recognition effectively in diverse environments. This paper presents a recognition system for multi-form Korean characters called RSMFK, which is based on the model of Hierarchical Temporal Memory (HTM). Our system can effectively recognize the printed Korean characters of different fonts, scales, rotation, noise and background. HTM is a model which simulates the neocortex of human brain to recognize and memorize intelligently. Experimental results show that RSMFK performs a good recognition rate of 97.8% on average, which is proved to be obviously improved over the conventional methods.

• Quantitative Bio-Science
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• v.37 no.2
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• pp.81-89
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• 2018

It is commonplace that high false detection rates interfere with immediate vision-based fire monitoring system. To circumvent this challenge, we propose a fire detection algorithm that can accommodate color variations of RGB in temporal domain, aiming at reducing false detection rates. Despite interrupting images (e.g., background noise and sudden intervention), the proposed method is proved robust in capturing distinguishable features of fire in temporal domain. In numerical studies, we carried out extensive real data experiments related to fire detection using 24 video sequences, implicating that the propose algorithm is found outstanding as an effective decision rule for fire detection (e.g., false detection rate <10%).