• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.40-48
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• 2012

This paper models the hue shift phenomenon and proposes a hue correction method to give perceptual matching between projector with and without additional white channel. To quantify the hue shift phenomenon for whole hue angle, 24 color patches with the same lightness are frist created along equally-spaced hue angle, and these are displayed one by one both displays with different luminance levels. Next, each hue value of the patches appeared on the projector with additional white channel is adjusted by observers until the hue values of patches on both displays appear the same visually. After obtaining the hue shift values from the color matching experiment, these values are piecewise fit into six polynomial functions, which approximately determine shifted hue amounts for an arbitrary hue values of each pixel in projector with additional white channel and are utilized to correct them. Actually, an input RGB image is converted to CIELAB LCH color space to get hue values of each pixel and this hue value is shifted as much as the amount calculated by the functions of hue shift model for correction. Finally, corrected image is inversely converted to an output RGB image. For an evaluation, the matching experiment with several test images and the z-score comparisons were performed.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.421-431
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• 2008

Recently XML is becoming a de facto standard for online data exchange between heterogeneous systems and also the research of streaming XML data filtering comes into the spotlight. Since streaming XML data filtering technique needs rapid matching of queries with XML data, it is required that the query processing should be efficiently performed. Until now, most of researches focused only on partial sharing of path expressions or efficient predicate processing and they were work for time and space efficiency. However, if containment relationship between queries is previously calculated and the lowest level query is matched with XML data, we can easily get a result that high level queries can match with the XML data without any other processing. That is, using this containment technique can be another optimal solution for streaming XML data filtering. In this paper, we suggest an efficient XML data filtering based on prime number indexing and containment relationship between queries. Through some experimental results, we present that our suggested method has a better performance than the existing method. All experiments have shown that our method has a more than two times better performance even though each experiment has its own distinct test purpose.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.341-356
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• 2016

Land information and building information have highest utilization and importance in real estate and city administration area. However, providing integrated information service was difficult because conflation and integrative utilization was not easy. In this study, necessity of integrated information system, direction of integration, method of conflation and design of integrated system for land and building information are presented. In addition, the prototype system is developed and possibility of application of integrated information is proposed. For this purpose, current situation of management of land and building information was analyzed. Based on the analysis, matching and conflation processes among spatial and attribute data were applied to land and building information. Using integrated land building information DB, integrated information system and functions were designed and the prototype system was constructed. At last, information service examples in real estate and city administration area were suggested through system operation by LX.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.121-130
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• 2010

As the development of wireless environment and portable devices, navigation companies need more spatial information for Location Based Service and so they are investing heavily in this part. But my country have constructed lots of spatial dataset during the NGIS project, and then we can reduce costs by using constructed spatial dataset. The integration method of each building information between e-AIS and KLIS-rn is linked to designed mapping table by main building numbers and auxiliary cadastral number. e-AIS and KLIS-rn are integrated by the feature matching between CAD data and KLIS-rn. Due to the limitation of test data, more accuracy test will be required with various data sets.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.130-145
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• 2021

As part of the Smart Seoul policy, the importance of using big urban data is being highlighted. Furthermore interest in the impact of transportation-related urban environmental factors such as PM10 and noise on citizen's quality of life is steadily increasing. This study established the integrated DB by matching IoT big data with transportation data, including traffic volume and speed in the microscopic Spatio-temporal scope. This data analyzed the impact of a spatial unit in the road-effect zone on environmental risk level. In addition, spatial units with similar characteristics of road traffic and environmental factors were clustered. The results of this study can provide the basis for systematically establishing environmental risk management of urban spatial units such as PM10 or PM2.5 hot-spot and noise hot-spot.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.577-587
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• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.113-120
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• 2005

3D reconstruction of a scene structure from un-calibrated image sequences has been long one of the central problems in computer vision. For 3D reconstruction in Euclidean space, projective reconstruction, which is classified into the merging method and the factorization, is needed as a preceding step. By calculating all camera projection matrices and structures at the same time, the factorization method suffers less from dia and error accumulation than the merging. However, the factorization is hard to analyze precisely long sequences because it is based on the assumption that all correspondences must remain in all views from the first frame to the last. This paper presents a new projective reconstruction method for recovery of 3D structure over long sequences. We break a full sequence into sub-sequences based on a quantitative measure considering the number of matching points between frames, the homography error, and the distribution of matching points on the frame. All of the projective reconstructions of sub-sequences are registered into the same coordinate frame for a complete description of the scene. no experimental results showed that the proposed method can recover more precise 3D structure than the merging method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.33-42
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• 2016

In Korea, the address-point matching technique has been used to provide geocoding services. In fact, this technique brings the high positional accuracy. However, the quality of geocoding result can be limited, since it is significantly affected by data quality. Also, it cannot be used for the 3D address geocoding and the reverse geocoding. In order to alleviate issues, the paper has implemeted proposed geocoding methods, based on street-based addresses matching technique developed by US census bureau, for street-based addresses in Korea. Those proposed geocoding methods are illustrated in two ways; (1) street address-matching method, which of being used for not only 2D addresses representing a single building but also 3D addresses representing indoor space or underground building, and (2) reverse geocoding method, whichas converting a location point to a readable address. The result of street-based address geocoding shows 82.63% match rates, while the result of reverse geocoding shows 98.5% match rates within approximately 1.7(m) the average position error. According to the results, we could conclude that the proposed geocoding techniques enable to provide the LBS(Location Based Service). To develop the geocoding methods, the study has perfoermed by ignoring the parsing algorithms for address standardization as well as the several areas with unusual addresses, such as sub-urban areas or subordinate areas to the roads, etc. In the future, we are planning the improved geocoding methods for considering these cases.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.507-512
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• 2001

Feature-based similarity has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects. the performance of conventional multidimensional data structures tends to deteriorate as the number of dimensions of feature vectors increase. The $R^{*}-Tree$ is the most successful variant of the R-Tree. In this paper, we propose a SOM-based $R^{*}-Tree$ as a new indexing method for high-dimensional feature vectors. The SOM-based $R^{*}-Tree$ combines SOM and $R^{*}-Tree$ to achieve search performance more scalable to high-dimensionalties. Self-Organizingf Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two-dimensional space. The map is called a topological feature map, and preserves the mutual relationships (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. We experimentally compare the retrieval time cost of a SOM-based $R^{*}-Tree$ with of an SOM and $R^{*}-Tree$ using color feature vectors extracted from 40,000 images. The results show that the SOM-based $R^{*}-Tree$ outperform both the SOM and $R^{*}-Tree$ due to reduction of the number of nodes to build $R^{*}-Tree$ and retrieval time cost.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.319-326
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• 2014

The accurate geo-referencing processes that apply ground control points is prerequisite for effective end use of HRSI (High-resolution satellite imagery). Since the conventional control point acquisition by human operator takes long time, demands for the automated matching to existing reference data has been increasing its popularity. Among many options of reference data, the airborne LiDAR (Light Detection And Ranging) data shows high potential due to its high spatial resolution and vertical accuracy. Additionally, it is in the form of 3-dimensional point cloud free from the relief displacement. Recently, a new matching method between LiDAR data and HRSI was proposed that is based on the image projection of whole LiDAR data into HRSI domain, however, importing and processing the large amount of LiDAR data considered as time-consuming. Therefore, we wmotivated to ere propose a local LiDAR chip generation for the HRSI geo-referencing. In the procedure, a LiDAR point cloud was rasterized into an ortho image with the digital elevation model. After then, we selected local areas, which of containing meaningful amount of edge information to create LiDAR chips of small data size. We tested the LiDAR chips for fully-automated geo-referencing with Kompsat-2 and Kompsat-3 data. Finally, the experimental results showed one-pixel level of mean accuracy.