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C-semantic: A Novel framework for next-generation robotic vision via the semantic web technologies

Currently, research in robotic vision faces numerous challenges, predominantly because of noisy sensor input and the processor hungry practices of object detection. Conventional machine vision algorithms are unable to handle real-time scenarios efficiently because they mostly rely on local storage f...

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Main Authors: Tang, A. Y. C., Azhana Ahmad, Alaaeddin Alweish, Mohd Sharifuddin Ahmad, Prof. Dr.
Format: Article
Language:English
Published: SCIENCEDOMAIN international 2017
Subjects:
Robotics
Online Access:http://dspace.uniten.edu.my:80/jspui/handle/123456789/37
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spelling my.uniten.dspace-372020-06-18T02:30:41Z C-semantic: A Novel framework for next-generation robotic vision via the semantic web technologies Tang, A. Y. C. Azhana Ahmad Alaaeddin Alweish Mohd Sharifuddin Ahmad, Prof. Dr. Robotics Currently, research in robotic vision faces numerous challenges, predominantly because of noisy sensor input and the processor hungry practices of object detection. Conventional machine vision algorithms are unable to handle real-time scenarios efficiently because they mostly rely on local storage for objects and a limited training process. In real life, there are endless number of objects which requires a huge storage capacities and a high level of hardware to handle real-time images quickly. In this paper, we address the challenges of current robotic vision and propose a novel framework (C-Semantic) based on cutting-edge semantic web technologies. The framework divides the entire robotic vision process into three functional layers in which each layer performs a set of predefined tasks. The process begins with a vocal command that is further converted into a SPARQL query. We design a C-Semantic ontology that semantically stores the domain information along with objects’ physical and geometrical features. The image-processing module of the framework receives an input image of an object and looks up for the object from the virtual environment by consulting the semantic features. An inference engine aids the image-processing 2017-05-08T03:05:31Z 2017-05-08T03:05:31Z 2016-02-17 Article 2231-0843 http://dspace.uniten.edu.my:80/jspui/handle/123456789/37 http://www.sciencedomain.org/abstract/13329 10.9734/BJAST/2016/23619 en British Journal of Applied Science & Technology SCIENCEDOMAIN international
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
topic Robotics
spellingShingle Robotics
Tang, A. Y. C.
Azhana Ahmad
Alaaeddin Alweish
Mohd Sharifuddin Ahmad, Prof. Dr.
C-semantic: A Novel framework for next-generation robotic vision via the semantic web technologies
description Currently, research in robotic vision faces numerous challenges, predominantly because of noisy sensor input and the processor hungry practices of object detection. Conventional machine vision algorithms are unable to handle real-time scenarios efficiently because they mostly rely on local storage for objects and a limited training process. In real life, there are endless number of objects which requires a huge storage capacities and a high level of hardware to handle real-time images quickly. In this paper, we address the challenges of current robotic vision and propose a novel framework (C-Semantic) based on cutting-edge semantic web technologies. The framework divides the entire robotic vision process into three functional layers in which each layer performs a set of predefined tasks. The process begins with a vocal command that is further converted into a SPARQL query. We design a C-Semantic ontology that semantically stores the domain information along with objects’ physical and geometrical features. The image-processing module of the framework receives an input image of an object and looks up for the object from the virtual environment by consulting the semantic features. An inference engine aids the image-processing
format Article
author Tang, A. Y. C.
Azhana Ahmad
Alaaeddin Alweish
Mohd Sharifuddin Ahmad, Prof. Dr.
author_facet Tang, A. Y. C.
Azhana Ahmad
Alaaeddin Alweish
Mohd Sharifuddin Ahmad, Prof. Dr.
author_sort Tang, A. Y. C.
title C-semantic: A Novel framework for next-generation robotic vision via the semantic web technologies
title_short C-semantic: A Novel framework for next-generation robotic vision via the semantic web technologies
title_full C-semantic: A Novel framework for next-generation robotic vision via the semantic web technologies
title_fullStr C-semantic: A Novel framework for next-generation robotic vision via the semantic web technologies
title_full_unstemmed C-semantic: A Novel framework for next-generation robotic vision via the semantic web technologies
title_sort c-semantic: a novel framework for next-generation robotic vision via the semantic web technologies
publisher SCIENCEDOMAIN international
publishDate 2017
url http://dspace.uniten.edu.my:80/jspui/handle/123456789/37
_version_ 1671342877630791680
score 13.211869

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