Galiano, Filipp and Zhukova, Nataly and Pelevin, Maksim (2014) Scenario Approach for Image Processing in Smart City. REAL CORP 2014 – PLAN IT SMART! Clever Solutions for Smart Cities. Proceedings of 19th International Conference on Urban Planning, Regional Development and Information Society. pp. 497-505.
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Text (Scenario Approach for Image Processing in Smart City)
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Abstract
Modern city is described by fast change of a situations and large volume of available data about it. One of principal data types are images (satellite pictures, video from surveillance cameras, etc.). Fast manual analysis of such data is often complicated or impossible. Widespread practice is development of analysis system for each separate problem (for example identification of car identification numbers or QR-codes) that leads to a number of difficulties; in particular, it is difficult to integrate and modify such systems. In article the structure of raster image analysis system (both single images and a video stream) is proposed. The system is developed taking into account peculiarities of input data and requirements imposed by the smart city. As a basis of system the set of algorithms, that implements all image analysis stages (preliminary processing, construction of feature space and classification) is proposed. That algorithms are elements of data processing scenarios. Usage of scenario approach, based on subject domain ontology, allows to significantly simplify adaptation of image processing system to the peculiarities of subject domain without limitation of allowed algorithms set. A example of application of the developed system for real-world problem is given.
Item Type: | Article |
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Uncontrolled Keywords: | image processing, pattern recognition, scenario approach, smart city, integration |
Subjects: | H Social Sciences > HD Industries. Land use. Labor Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TR Photography |
Depositing User: | REAL CORP Administrator |
Date Deposited: | 26 Jul 2016 14:55 |
Last Modified: | 26 Jul 2016 14:55 |
URI: | http://repository.corp.at/id/eprint/255 |
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