• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.540-546
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• 2019

This study suggests a binarization method that minimizes information loss for night illumination images. The object of the night illumination image is an image which is not focused due to the influence of illumination and is not identifiable. Also, the image has a brightness area in only a part of the brightness histogram. So the existing simple binarization method is hard to get good results. The proposed binarization method uses image segmentation method and image merging method. In the stepwise divided blocks, we divide into two regions using the triangular type of fuzzy logic. The value 0 of the membership degree is binarized at the present step, and the value of the membership degree 1 is binarized after the next step. Experimental results show that night illumination images with minimal loss of information can be obtained in a dark area brightness range.

• Journal of KIISE
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• v.43 no.12
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• pp.1428-1436
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• 2016

A multipath routing in wireless sensor networks (WSNs) provides advantage such as reliability improvement and load balancing by transmitting data through divided paths. For these reasons, existing multipath routing protocols divide path appropriately or create independent paths efficiently. However, when the sink node moves to avoid hotspot problem or satisfy the requirement of the applications, the existing protocols have to reconstruct multipath or exploit foot-print chaining mechanism. As a result, the existing protocols will shorten the lifetime of a network due to excessive energy consumption, and lose the advantage of multipath routing due to the merging of paths. To solve this problem, we propose a multipath creation and maintenance scheme to support the mobile sink node. The proposed protocol can be used to construct local grid structure with restricted area and exploit grid structure for constructing the multipath. The grid structure can also be extended depending on the movement of the sink node. In addition, the multipath can be partially reconstructed to prevent merging paths. Simulation results show that the proposed protocol is superior to the existing protocols in terms of energy efficiency and packet delivery ratio.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1275-1288
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• 2015

A microscale weather analysis module (about 1km or less) is a microscale numerical weather prediction model designed for operational forecasting and atmospheric research needs such as radiant energy, thermal energy, and humidity. The accuracy of the module is directly related to the usefulness and quality of real-time microscale weather information service in the metropolitan area. This paper suggests an object based verification method useful for spatio-temporal evaluation of the accuracy of the microscale weather analysis module. The method is a graphical method comprised of three steps that constructs a lattice field of evaluation statistics, merges and identifies objects, and evaluates the accuracy of the module. We develop lattice fields using various evaluation spatio-temporal statistics as well as an efficient object identification algorithm that conducts convolution, masking, and merging operations to the lattice fields. A real data application demonstrates the utility of the verification method.

• Journal of Korea Water Resources Association
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• v.48 no.9
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• pp.719-728
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• 2015

In this study, urban runoff analyses were performed using high resolution Quantitative Precipitation Estimation (QPE), and variation of rainfall and runoff were analyzed to evaluate QPE data for urban runoff analysis. The five drainage districts (Seocho3, 4, 5, Yeoksam and Nonhyun) around Gangnam station were chosen as study area, the area is $7.4km^2$. Rainfall data from KMA AWS (34 stations), SKP AWS (156 stations) and Gwanduk radar were used for QPEs in Seoul area. Four types of QPE(QPE1: KMA AWS, QPE2: KMA+ SKP AWS, QPE3: Gwangduk radar, QPE4: QPE2+QPE3) of 6 events in July 2013 were generated by using Krigging and conditional merging. The temporal and spatial resolution of QPEs are 10 minutes and 250 m, respectively. The complex pipe network were treated as 773 manholes, 772 sub-drainage districts and 1,059 pipelines for urban runoff analysis as input data. QPE2 and QPE4 show spatial variation of rainfall by sub-drainage districts as 1.9 times bigger than QPE1. The peak runoff of QPE2 and QPE4 also show spatial variation as 6 times bigger than Gangnam and Seocho AWS. Thus, the spatial variation of rainfall and runoff could exist in small area such as this study area, and using high-resolution rainfall data is desirable for accurate urban runoff analysis.

• Journal of Navigation and Port Research
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• v.26 no.1
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• pp.95-100
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• 2002

The first version of KHCM was Published in 1992 and is currently used in engineering Practice extensively. The study of new manual was initiated by Korea Institute of Construction Technology 1998 and is intended to be ready for publication by the year 2002. According to the field survey, the action of the individual merging vehicle creates turbulence in the vicinity of the ramp-freeway junction area. The purpose of this paper is to develop the model for Predicting the for entering the lanes 1 and 2($V_{12}$) and the density function at the influence zone by comがring the research works on the ramp junction in the USHCM 2000. The methodology has two major steps : the determination of the flow entering Lanes 1 and 2 immediately upstream of the merge influence area: and the density of the flow within the ramp influence area As a result of this paper the specific functions for such models are suggested through the regression analysis of data collected at four freeway fields in Korea.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.103-112
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• 2019

Extraction of region of interest for satellite image classification is one of the important techniques for efficient management of the national land space. However, recent studies on satellite image classification often depend on the information of the selected image in selecting the region of interest. This study propose an effective method of selecting the area of interest using the continuous digital topographic map constructed from high resolution images. The spatial information used in this research is based on the digital topographic map from 2013 to 2017 provided by the National Geographical Information Institute and the 2015 Sejong City land cover map provided by the Ministry of Environment. To verify the accuracy of the extracted area of interest, KOMPSAT-3A satellite images were used which taken on October 28, 2018 and July 7, 2018. The baseline samples for 2015 were extracted using the unchanged area of the continuous digital topographic map for 2013-2015 and the land cover map for 2015, and also extracted the baseline samples in 2018 using the unchanged area of the continuous digital topographic map for 2015-2017 and the land cover map for 2015. The redundant areas that occurred when merging continuous digital topographic maps and land cover maps were removed to prevent confusion of data. Finally, the checkpoints are generated within the region of interest, and the accuracy of the region of interest extracted from the K3A satellite images and the error matrix in 2015 and 2018 is shown, and the accuracy is approximately 93% and 72%, respectively. The accuracy of the region of interest can be used as a region of interest, and the misclassified region can be used as a reference for change detection.

• Publications of The Korean Astronomical Society
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• v.22 no.2
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• pp.43-54
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• 2007

Many gravitational wave detectors are now being built or under operation throughout the world. In particular, LIGO has taken scientific data several times, although current sensitivity is not sufficient to detect the weak signals routinely. However, the sensitivities have been improving steadily over past years so that the real detection will take place in the near future. Data analysis is another important area in detecting the gravitational wave signal. We have carried out the basic research in order to implement data analysis software in Korea@home environment. We first studied the LIGO Science Collaboration Algorithm Library(LAL) software package, and extracted the module that can generate the virtual data of gravitational wave detector. Since burst sources such as merging binaries of neutron stars and black holes are likely to be detected first, we have concentrated on the simulation of such signals. This module can generate pure gravitational wave forms, noise suitable for LIGO, and combination of the signal and noise. In order to detect the gravitational signal embedded in the noisy data, we have written a simple program that employs 'matched filtering' method which is very effective in detecting the signal with known waveform. We found that this method works extremely well.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.8-19
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• 2004

In this paper, we propose an efficient method for locating destination address block on both of machine-Printed and handwritten Korean mail piece images. The proposed method extracts connected components from the binary mail piece image, generates text lines by merging them, and then groups the text fines into nine clusters. The destination address block is determined by selecting some clusters. Considering the geometric characteristics of address information on Korean mail piece, we split a mail piece image into nine areas with an equal size. The nine clusters are initialized with the center coordinate of each area. A modified Manhattan distance function is used to compute the distance between text lines and clusters. We modified the distance function on which the aspect ratio of mail piece could be reflected. The experiment done with live Korean mail piece images has demonstrated the superiority of the Proposed method. The success rate for 1, 988 testing images was about 93.56%.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.123-137
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• 2011

In general, flow propagation has been explained using the shock wave theory which is expressed as a function of variations in volume and density. However, the theory has certain limitation in portraying heterogeneous flow, e.g., flow propagation between lanes. Motivated by this fact, this study seeks a new measure for analyzing the propagation characteristics of traffic flow at three sections of highway (i.e., merging area, weaving section, and basic section) from temporal and spatial perspectives, and then develops a model for estimating the measure for the flow propagation. The "shock wave speed" which is the measure widely adopted in literature, was first applied to describe the propagation characteristics, but it was hard to find distinct characteristics in the propagation. This finding inspires to develop a new measure named "Impulse Volume". It is shown that the measure better explains the propagation characteristics at the three study sections of highway. In addition, several models are also developed by performing multi-regression analyses to explain the flow propagation between lanes. The models proposed in this paper can be distinguished in three sections and the lane placement.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.11-20
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• 2010

In this paper we propose a face detection system which consists of a method of face candidate extraction using skin color and a method of face verification using the feature of facial structure. Firstly, the proposed extraction method of face candidate uses the image segmentation and merging algorithm in the regions of skin color and the neighboring regions of skin color. These two algorithms make it possible to select the face candidates from the variety of faces in the image with complicated backgrounds. Secondly, by using the partial face classifier, the proposed face validation method verifies the feature of face structure and then classifies face and non-face. This classifier uses face images only in the learning process and does not consider non-face images in order to use less number of training images. In the experimental, the proposed method of face candidate extraction can find more 9.55% faces on average as face candidates than other methods. Also in the experiment of face and non-face classification, the proposed face validation method obtains the face classification rate on the average 4.97% higher than other face/non-face classifiers when the non-face classification rate is about 99%.