• Journal of Cadastre & Land InformatiX
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• v.44 no.1
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• pp.127-138
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• 2014

It can be effective to extract and apply the updated information from the newly updated map data for updating road data of topographic map. In this study, update target data and update reference data are overlaid and the update objects are explored using network matching technique. And the network objects are classified into five matching and update cases and the update processes for each case are applied to the test data. For this study, road centerline data of digital topographic map is used as an update target data and road data of Korean Address Information System is used as an update reference data. The buffer-based network matching method is applied to the two data and the matching and update cases are classified after calculating the overlaid ratio of length. The newly updated road centerline data of digital topographic map is generated from the application of update process for each case. As a result, the update information can be extracted from the different map dataset and applied to the road network data updating.

• Journal of KIISE
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• v.44 no.4
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• pp.392-398
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• 2017

The point-cloud representation of an object is performed by scanning a space through a laser scanner that is extracting a set of points, and the points are then integrated into the same coordinate system through a registration. The set of the completed registration-integrated point clouds is classified into meaningful regions, shapes, and noises through a mathematical analysis. In this paper, the aim is the matching of a curved area like a cylinder shape in 3D point-cloud data. The matching procedure is the attainment of the center and radius data through the extraction of the cylinder-shape candidates from the sphere that is fitted through the RANdom Sample Consensus (RANSAC) in the point cloud, and completion requires the matching of the curved region with the Catmull-Rom spline from the extracted center-point data using the Principal Component Analysis (PCA). Not only is the proposed method expected to derive a fast estimation result via linear and curved cylinder estimations after a center-axis estimation without constraint and segmentation, but it should also increase the work efficiency of reverse engineering.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.279-284
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• 2004

Fingerprints have been widely used in the biometric authentication because of its performance, uniqueness and universality. Recently, the speed of identification becomes a very important point in the fingerprint-based security applications. Also, the reliability still remains the main issue in the fingerprint identification. In this paper, we propose the fast and reliable fingerprint matching algorithm based on the process of the 'self-nonself' discrimination in the biological immune system. The proposed algorithm is organized by two-matching stage. The 1st matching stage does the matching process by the use of the 'self-space' and MHC detector string set that are generated from the minutiae and the values of the directional field. Then the 2nd matching stage is made based on the local-structure of the minutiae. The proposed two matching stage reduces matching time while the reliability of the matching algorithm is maintained.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.127-136
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• 2010

In multi-view video, illumination disharmony between neighboring views can occur on account of different location of each camera and imperfect camera calibration, and so on. Such discrepancy can be the cause of the performance decrease of multi-view video coding by mismatch of inter-view prediction which refer to the pictures obtained from the neighboring views at the same time. In this paper, we propose an efficient histogram-based prefiltering algorithm to compensate mismatches between the luminance and chrominance components in multi-view video for improving its coding efficiency. To compensate illumination variation efficiently, all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching. A Cosited filter that is used for chroma subsampling in many video encoding schemes is applied to each color component prior to histogram matching to improve its performance. The histogram matching is carried out in the RGB color space after color space converting from YCbCr color space. The effective color conversion skill that has respect to direction of edge and range of pixel value in an image is employed in the process. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with other methods.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.2
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• pp.67-74
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• 2013

Approximate string matching problems have been studied in diverse fields. Recently, fast approximate string matching algorithms are being used to reduce the time and costs for the next generation sequencing. To measure the amounts of errors between two strings, we use a distance function such as the edit distance. Given two strings X(|X| = m) and Y(|Y| = n) over an alphabet ${\Sigma}$, the edit distance between X and Y is the minimum number of edit operations to convert X into Y. The edit distance between X and Y can be computed using the well-known dynamic programming technique in O(mn) time and space. The edit distance also can be computed using the Four-Russians' algorithm whose preprocessing step runs in $O((3{\mid}{\Sigma}{\mid})^{2t}t^2)$ time and $O((3{\mid}{\Sigma}{\mid})^{2t}t)$ space and the computation step runs in O(mn/t) time and O(mn) space where t represents the size of the block. In this paper, we present a parallelized version of the computation step of the Four-Russians' algorithm. Our algorithm computes the edit distance between X and Y in O(m+n) time using m/t threads. Then we implemented both the sequential version and our parallelized version of the Four-Russians' algorithm using CUDA to compare the execution times. When t = 1 and t = 2, our algorithm runs about 10 times and 3 times faster than the sequential algorithm, respectively.

• Journal of the Korean Regional Science Association
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• v.38 no.2
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• pp.21-41
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• 2022

The purpose of this study is to compare the differences in the subjective quality of life (QoL) perceived by residents in different settlement spaces such as urban vs. rural and Seoul Capital Area (SCA) vs. Non-Capital Area (NCA). Using the data of the 'Quality of Life Satisfaction Survey for Balanced Development' conducted nationwide by the Presidential Committee for Balanced National Development in 2018, a propensity score matching method was introduced to compare the differences between the types of settlement spaces. The results show that no significant difference is found between all the types in satisfaction with local life, and in the case of happiness, rural residents show a higher level than those living in cities. Looking at the quality of life by QoL domain, the QoL of urban residents in SCA is generally the highest in the basic living environment, medical care, and culture/leisure domains, while the QoL of rural residents in the job/income, environment, community, and welfare domains is higher than that of residents of SCA and NCA cities. Interestingly, in no domains NCA cities show their relative strength. These results show the value of rural areas in the face of increasingly prevailing urbanization trends, and suggests that the value of rural areas must be strengthened for rural development. It is necessary to pursue policy efforts such as rural regeneration based on spatial planning in order to respond to the disorganized development that damages the value of the rural environment and landscape and to harmoniously maintain and develop the rural settlement.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.295-296
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• 2008

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.117-117
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• 2004

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.161-162
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• 2012

국토공간정보의 효율적인 관리를 위하여 지형공간정보와 시설물의 정확한 위치정보의 수집이 가장 기본적으로 요구되며 이는 지능형 국토정보의 구축 및 운영을 위해서 가장 중요하면서도 많은 작업량을 포함하기 마련이다. 이러한 국토공간정보는 도시계획 및 통신계획, 대규모 건설, 건축, 입체적인 도시정보시스템 구현, 안전 및 방재 등에서 많은 필요와 그 중요성이 크게 부각되고 있다. 본 연구에서는 건설현장의 환경정보 수집과 더불어 구조물의 정보 수집을 위하여 USN를 이용하여 기존의 항공사진과 DEM의 매칭에 의한 지형공간정보와 비교하였으며 이를 분석하여 새로운 건설공사에서의 공간정보를 실시간으로 취득하여 이용할 수 있는 기법을 제시하였다.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.105-118
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• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.