• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1518-1524
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• 2014

In this paper, a new method of spatial query, which is called Surround Search (SuSe) is suggested. This method makes it possible to search for the closest spatial object of interest to the user from a query point. SuSe is differentiated from the existing spatial object query schemes, because it locates the closest spatial object of interest around the query point. While SuSe searches the surroundings, the spatial object is saved on an R-tree, and MINDIST, the distance between the query location and objects, is measured by considering an angle that the existing spatial object query methods have not previously considered. The angle between targeted-search objects is found from a query point that is hidden behind another object in order to distinguish hidden objects from them. The distinct feature of this proposed scheme is that it can search the faraway or hidden objects, in contrast to the existing method. SuSe is able to search for spatial objects more precisely, and users can be confident that this scheme will have superior performance to its predecessor.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.37-43
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• 2022

Drones, one of the 4th industrial technologies that are expanding from military use to industrial use, are being actively used in the search missions of the National Police Agency and finding missing persons, thereby reducing interest in a wide area and the input of large-scale search personnel. However, legal review of police drone operation is continuously required, and the importance of advanced system for related operations and analysis of captured images in connection with search techniques is increasing at the same time. In this study, in order to facilitate recording, preservation, and monitoring in the concept of precise search and monitoring, it is possible to achieve high efficiency and secure golden time when precise search is performed by constructing spatial information based on photo rather than image data-based search. Therefore, we intend to propose a spatial information construction technique that reduces the resulting data volume by adjusting the unnecessary spatial information completion rate according to the size of the subject. Through this, the scope of use of drone search missions for large-scale areas is advanced and it is intended to be used as basic data for building a drone operation manual for police searches.

• Spatial Information Research
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• v.5 no.2
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• pp.195-198
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• 1997

The his paper describes Management System of Environment GIS Data using JVM, JDBC, Oracle DB. Environment GIS data using the system are satellite Image, Thematic Map, GIS Data. The data have spatial information and attribute information. The search supplies spatial search using viewing-map on Web browser, nonspatial search using the attributes of data. The registration of data use the registration system of data on Web browser.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.185-196
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• 2018

In order to overcome the problem that outdoor and indoor spatial information service are separately utilized, an integration service system of spatial information that is linked from outdoor to indoor has been implemented. As a result of the study, "0001.xml" corresponding to the file index key value, which is the service connection information in the building information of the destination, was extracted from the prototype verification of the system, the search word of 'Kim AB' was transmitted to the indoor map server and converted from the outdoor map service to the indoor map service through confirmation of the navigation service connected information, using service linkage information and search words of the indoor map service was confirmed that the route was displayed from the entrance of the building to the destination in the building through the linkage search DB (Database) table and the search query. Therefore, through this study was examined the possibility of linking indoor and outdoor DB through vector spatial information integration service system. The indoor map and the map engine were implemented based on the same vector map format as the outdoor map engine, it was confirmed that the connectivity of the map engine can be applied.

• Korean Journal of Cognitive Science
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• v.16 no.3
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• pp.155-174
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• 2005

Oh and Kim (2004) and Woodman and Lurk (2004) demonstrated that spatial working memory (SWM) load Interfered concurrent visual search and that search process also impaired the maintenance of spatial information implying that visual search and SWM task both require access to the same limited-capacity mechanism. Two obvious possibilities have been suggested about what this shared limited-capacity mechanism is: common demand for attention to the locations where the items f9r the two tasks were presented (spatial attention load hypothesis), and common use of working memory to maintain a record of locations have been processed(SWM load hypothesis). To test these two hypothetical explanations, Experiment 1 replicated the mutual interference between visual search and SWM task in spite of difference of procedure with preceding researches; possible areas where the items for two tasks were presented were not separated. In Experiment 2, we presented the items for visual search either in the same quadrants where the items for SWM task had appeared (same-location rendition) or in the different quadrants (different-location condition). As a result, search efficiency was more impaired in the different-location condition than in the same-location condition. The memory accuracy was worse in the different-location rendition than in the same-location rendition. Overall results of study indicate that the mutual interference between SWM and visual search might be related to the overload of spatial attention, but not to that of SWM.

• Spatial Information Research
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• v.18 no.4
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• pp.109-120
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• 2010

Recently, due to rapid increasement of spatial data collected from various geosensors in u-GIS environments, the importance of spatial index for efficient search of large spatial data is rising gradually. Especially, researches based R-Tree to improve search performance of spatial data have been actively performed. These previous researches focus on reducing overlaps between nodes or the height of the R -Tree. However, these can not solve an unnecessary node access problem efficiently occurred in tree traversal. In this paper, we propose a MR-Tree(Mapping-based R-Tree) to solve this problem and to support efficient search of large spatial data. The MR-Tree can improve search performance by using a mapping tree for direct access to leaf nodes of the R-Tree without tree traversal. The mapping tree is composed with MBRs and pointers of R-Tree leaf nodes associating each partition which is made by splitting data area repeatedly along dimensions. Especially, the MR-Tree can be adopted in various variations of the R-Tree easily without a modification of the R-Tree structure. In addition, because the mapping tree is constructed in main memory, search time can be greatly reduced. Finally, we proved superiority of MR-Tree performance through experiments.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.318-324
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• 2001

In this paper we propose the adaptive scheme to place more search points as long as the operation tapability of the motion estimator in the video codec permits. And the proposed algorithm takes advantage of the intuitive fact that the quality of the decoded video is more degraded as the spatial frequency of the corresponding block is increased due to the augmentation of local minima per unit area. Thererore, we propose the scheme to enhance the quality by locating relatively more search points in the block with high frequency components by analyzing the spatial frequencies of the video sequence. As a result, the proposed scheme can adaptively place more search points possibly permitted by the motion estimator and guarantees better quality compared to the TSS and FS.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2173-2184
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• 1997

Among spatial queries handled in spatial database systems, nearest neighbor queries to find the nearest spatial object from the given locaion occur frequently. The number of searched nodes in an index must be minimized in order to increase the performance of nearest neighbor queries. An Existing approach considered only the processing of an nearest neighbor query in a two-dimensional search space and could not optimize the number of searched nodes accurately. In this paper, we propose the optimal search distance and prove its properties. The proposed optimal search distance is the measurement of a new search distance for accurately selecting the nodes which will be searched in processing nearest neighbor queries. We present an algorithm for processing the nearest neighbor query by applying the optimal search distance to R-trees and prove that the result of query processing is correcter than the existing approach.

• Journal of Korean Society for Geospatial Information Science
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• v.3 no.2 s.6
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• pp.137-149
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• 1995

A spatial index is necessary to support an efficient search in a geographical information system (GIS) that is important in these days. In this paper, we design and implement a geographical data manager, called GOOD (Geo-object Oriented Data Manager) 2.0, by extending GOOD 1.0 with a spatial index processing module. That is, R-tree and R*-tree are used as a spatial index in this paper to make an efficient search possible. In addition, this paper conducts a performance evaluation to measure the improvement in search efficiency and analyzes the results of the performance evaluation. When the performance evaluation is carried out, we consider various environment factors to allow an GIS administrator to use the results as a basic data in selecting an appropriate spatial index.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.43-46
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• 2000

In this paper, we propose a fast adaptive diamond search algorithm(FADS) for block matching motion estimation. Fast motion estimation algorithms reduce the computational complexity by using the UESA (Unimodal Error Search Assumption) that the matching error monotonically increases as the search moves away from the global minimum error. Recently many fast BMAs(Block Matching Algorithms) make use of the fact that the global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the adjacent blocks. We change the origin of search window according to the spatially adjacent motion vectors and their MAE(Mean Absolute Error). The computer simulation shows that the proposed algorithm has almost the same computational complexity with UCBDS(Unrestricted Center-Biased Diamond Search)〔1〕, but enhance PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS(Full Search), even for the large motion case, with half the computational load.