• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.80-87
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• 2004

In this paper we proposed the novel feature extraction method that is able to extract the individual characters from the license plate area of the car image more precisely by using the RGB color information and the fuzzy binarization newly proposed. The proposed method, first, extracts from the original image the areas that the pixels with the colors around the green are concentrated on as the candidate areas of the license plate, and selects the area with the most intensive distribution of pixels with the white color among the candidate areas as the license plate area. Second the noises of the license plate area should be removed by using 34{\times}$3 Sobel masking, and the fuzzy binarization method are proposed and applied to the license plate area to generate the binarized image of the license plate area. Lastly, the application of the contour tracking algorithm to the binarized area extracts the individual characters from the license plate area. The experiment on a variety of the real car images showed that the proposed method generates the higher rate of success for character extraction than the previous methods.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.10
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• pp.1417-1426
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• 2001

Turbulent flow characteristics in the near wake of a square cylinder have been studied experimentally by using a Digital PIV method. Experiments are performed at the Reynolds numbers of 1600 and 3900 based on the free-stream velocity and the square height. The ensemble averaged turbulence statistics are acquired from 2030 realizations of instantaneous fluctuating velocity field after the conventional Reynolds decomposition. The differences in turbulent intensity and Reynolds shear stress profiles fur both oases indicate that the effect of Reynolds number seems to be descernible mainly due to the occurrence of transition in the separated shear layer. Because of the periodic nature of vortex shedding process, transverse velocity fluctuations contribute dominantly , to turbulent kinetic energy distribution. A comparison with previous LDV data obtained at much higher Reynolds number shows a fairly good agreement each other. It turns out that the effect of Reynolds number diminishes as increasing Reynolds number, which is a well-known feature of a sharp-edged bluff body wake. The streamwise variation of turbulence intensities are compared with those from a circular cylinder along the centerline at the same Reynolds number. The overall magnitudes and the decay rates of turbulence intensities are quite similar, but some differences are noticeble especially in the transverse intensity variation.

• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.971-976
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• 2018

An accurate analysis of pipeline transient is important for proper management and operation of a water distribution systems. The computational accuracy and its cost are two distinct components for unsteady flow analysis model, which can be strength and weakness of three-dimensional model and one-dimensional model, respectively. In this study, we used two-dimensional unsteady flow model with Five-Region Turbulence model (FRTM) with the implementation of interaction between liquid and air Since FRTM has an empirical component to be determined, we explored the response feature of two-dimensional flow model. The relationship between friction behaviour and the variation of undetermined parameter was configured through the comparison between numerical simulations and experimental results.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.303-310
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• 2007

In machine learning, the ensemble classifier that is a set of classifiers have been introduced for higher accuracy than individual classifiers. We propose a new ensemble learning method that employs a set of region based classifiers. To show the performance of the proposed method. we compared its performance with that of bagging and boosting, which ard existing ensemble methods. Since the distribution of data can be different in different regions in the feature space, we split the data and generate classifiers based on each region and apply a weighted voting among the classifiers. We used 11 data sets from the UCI Machine Learning Repository to compare the performance of our new ensemble method with that of individual classifiers as well as existing ensemble methods such as bagging and boosting. As a result, we found that our method produced improved performance, particularly when the base learner is Naive Bayes or SVM.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.1-6
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• 2001

Eigenface method in face recognition is useful due to its insensitivity to large variations in facial expression and facial details. However its low recognition rate necessitates additional researches. In this paper, we present an efficient method for improving the recognition rate in face recognition using eigenface feature. For this, we performs a comparative study of three different classifiers which are i) a single prototype (SP) classifier, ii) a nearest neighbor (NN) classifier, and iii) a standard feedforward neural network (FNN) classifier. By evaluating and analyzing the performance of these three classifiers, we shows that the distribution of eigenface features of face image is not compact and that selections of classifier and sample training data are important for obtaining higher recognition rate. Our experiments with the ORL face database show that 1-NN classifier outperforms the SP and FNN classifiers. We have achieved a recognition rate of 91.0% by selecting sample trainging data properly and using 1-NN classifier.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.1-8
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• 2003

Various methods have been studying to maintain and apply the multimedia inform abruptly increasing over all social fields, in recent years. For retrieval of still images, we is implemented content-based image retrieval system in this paper that make possible to retrieve similar objects from image database after segmenting query object from background if user request query. Query image is processed median filtering to remove noise first and then object edge is detected it by canny edge detection. And query object is segmented from background by using convex hull. Similarity value can be obtained by means of histogram intersection with database image after securing color histogram from segmented image. Also segmented image is processed gray convert and wavelet transform to extract spacial gray distribution and texture feature. After that, Similarity value can be obtained by means of banded autocorrelogram and energy. Final similar image can be retrieved by adding upper similarity values that it make possible to not only robust in background but also better correct object retrieval by using object segmentation method.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.64-75
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• 2008

Since the current database systems for managing geotechnical investigation results were limited by being described boring test result in point feature, it has been trouble for using other GIS data. Although there are some studies for spatial characteristics of subsurface modeling, it is rather lack of being interoperable with GIS, considering geotechnical engineering facts. This is reason for difficulty of practical uses. In this study, we has developed subsurface spatial information model through extracting needed geotechnical engineering data from geotechnical information DB. The developed geotechnical information clustering program(GEOCL) has made a cluster of boring formation(and formation ratio), classification of layer, and strength characteristics of subsurface. The interpolation of boring data has been achieved through zonal kriging method in the consideration of spatial distribution of created cluster. Finally, we make a subsurface spatial information model to integrate with digital elevation model, and visualize 3-dimensional model by subsurface spatial information viewing program(SSIVIEW). We expect to strengthen application capacity of developed model in subsurface interpretation and foundation design of construction works.

• Journal of Microbiology and Biotechnology
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• v.27 no.11
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• pp.1942-1951
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• 2017

Campylobacter jejuni and Campylobacter coli are important foodborne pathogenic bacteria, particularly in poultry meat. In this study, the presence of extracellular DNase activity was investigated for biofilm-deficient Campylobacter strains versus biofilm-forming Campylobacter strains isolated from chickens, to understand the relationship between extracellular DNase activity and biofilm formation. A biofilm-forming reference strain, C. jejuni NCTC11168, was co-incubated with biofilm non-forming strains isolated from raw chickens or their supernatants. The biofilm non-forming strains or supernatants significantly prohibited the biofilm formation of C. jejuni NCTC11168. In addition, the strains degraded pre-formed biofilms of C. jejuni NCTC11168. Degradation of C. jejuni NCTC11168 biofilm was confirmed after treatment with the supernatant of the biofilm non-forming strain 2-1 by confocal laser scanning microscopy. Quantitative analysis of the biofilm matrix revealed reduction of extracellular DNA (16%) and proteins (8.7%) after treatment. Whereas the biofilm-forming strains C. jejuni Y23-5 and C. coli 34-3 isolated from raw chickens and the C. jejuni NCTC11168 reference strain showed no extracellular DNase activity against their own genomic DNA, most biofilm non-forming strains tested, including C. jejuni 2-1, C. coli 34-1, and C. jejuni 63-1, exhibited obvious extracellular DNase activities against their own or 11168 genomic DNA, except for one biofilm non-former, C. jejuni 22-1. Our results suggest that extracellular DNase activity is a common feature suppressing biofilm formation among biofilm non-forming C. jejuni or C. coli strains of chicken origin.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.87-100
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• 2003

Most of statistical data are generated by a set of dynamic, stochastic, and simultaneous relations. An important question is how to specify statistical models so that they are consistent with the dynamic feature of those data. A general hypothesis is that the lagged effect of a change in an explanatory variable is not felt all at once at a single point in time, but The impact is distributed over a number of future points in time. In other words, current control variables are determined by a function that can be reduced to a distributed lag function of past observations. It is possible to explain the relationship between variables in different points of time and to estimate the long-run impacts of a change in a variable on another if time lag series of explanatory variables are incorporated in the model specification. In this study, distributed lag structure is applied to the domestic stock market model to capture the dynamic response of the market by exogenous shocks. The Domestic market is found more responsive to the changes in foreign market factors both in the short and the long run.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.87-100
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• 2011

In this paper, we address a video summarization task as generating both visually salient and semantically important video segments. In order to find salient data points, one can use the OC-SVM (One-class Support Vector Machine), which is well known for novelty detection problems. It is, however, hard to incorporate into the OC-SVM process the importance measure of data points, which is crucial for video summarization. In order to integrate the importance of each point in the OC-SVM process, we propose a fuzzy version of OC-SVM. The Importance-based Fuzzy OC-SVM weights data points according to the importance measure of the video segments and then estimates the support of a distribution of the weighted feature vectors. The estimated support vectors form the descriptive segments that best delineate the underlying video content in terms of the importance and salience of video segments. We demonstrate the performance of our algorithm on several synthesized data sets and different types of videos in order to show the efficacy of the proposed algorithm. Experimental results showed that our approach outperformed the well known traditional method.