Researches on the Object-Oriented Model of Distributed Image Database

2014 ◽  
Vol 543-547 ◽  
pp. 2184-2187
Author(s):  
Ping Zhang Gou ◽  
Yong Zhong Tang
Keyword(s):  
Comparative Analysis ◽  
Data Model ◽  
Object Oriented ◽  
Image Data ◽  
Image Database ◽  
Management Modes

Combined with the characteristics of the image data, this study contrasted four kinds of data model. Then it analyzed the three kinds of realization methods of image database, comparative analysis of management modes of the distributed image database finally.

scholarly journals HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEW

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1295-1299
Author(s):  
M. Du ◽  
J. Wang ◽  
C. Jing ◽  
J. Jiang ◽  
Q. Chen
Keyword(s):  
Data Model ◽  
Image Data ◽  
Urban Infrastructure ◽  
Hierarchical Data ◽  
Urban Management ◽  
Important Research ◽  
Multiple Cameras ◽  
Street View ◽  
Image Capturing ◽  
Real Test

<p><strong>Abstract.</strong> Maintaining an up-to-date inventory of urban infrastructure such as fire hydrant is critical to urban management. Street view database such as Google Street View and Baidu Street View contain street-level images, their potential for urban management has not been fully explored. For the massive image, data model for storage and indexing is an important research issue. Considering multiple cameras and GPS device in the image capturing platform, a hierarchical data model named 3D-Grid is proposed. Massive street view images were stored according to grid ID, GPS time and camera ID. An efficient time indexing algorithm is brought forth to replace the spatial indexing. Real test experiments are conducted in a project, and the validation and feasibility of 3D-Grid including time indexing algorithm were validated.</p>

An Image Data Model

2000 ◽  
pp. 14-25 ◽  
Author(s):  
William I. Grosky ◽  
Peter L. Stanchev
Keyword(s):  
Data Model ◽  
Image Data

scholarly journals Sharing brain mapping statistical results with the neuroimaging data model

2016 ◽  
Author(s):  
Camille Maumet ◽  
Tibor Auer ◽  
Alexander Bowring ◽  
Gang Chen ◽  
Samir Das ◽  
...  
Keyword(s):  
Data Model ◽  
Image Data ◽  
Software Packages ◽  
Fmri Study ◽  
Neuroimaging Data ◽  
Neuroimaging Software ◽  
Meta Analyses ◽  
Machine Readable ◽  
Univariate Analyses ◽  
Statistical Results

AbstractOnly a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a format specification providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standardized representation allows authors to relay methods and results in a platform-independent regularized format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publically available at: http://nidm.nidash.org/specs/nidm-results.html.

Storage and Management Approach of Raster Image in Georaster Model

2013 ◽  
Vol 380-384 ◽  
pp. 3479-3482
Author(s):  
Guang Shi Li ◽  
Ming Yang ◽  
Ji Li
Keyword(s):  
Data Model ◽  
Image Data ◽  
Divide And Conquer ◽  
Management Approach ◽  
Vector Data ◽  
Oracle Spatial ◽  
Raster Image ◽  
Data Capacity ◽  
Network Transmission ◽  
Transmission Speed

The putting forward of Georaster brings a new opportunity for realizing integrated storage of raster data and vector data in Oracle Spatial . This paper analyzed raster images storage and management mechanisms using Georaster model of Oracle spatial, including GeoRester data model,physical storage structure, data block and pyramid strategy. On this basis, the paper demonstrated a typical example of storing and managing raster image data. Through a large number of experiments, the paper pointed out that the Oracle's raster image data loading tool cannot upload large capacity raster image. Aiming at the disadvantage in terms of data capacity, the paper presented a simple yet effective solution, which adopts block processing way, is consistent with "divide and conquer idea, can improve data processing and network transmission speed.

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