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AN ONTOLOGY-DRIVEN VEGETATION CLASSIFICATION FOR SEMANTIC-BASED IMAGE RETRIEVAL OF AERIAL PHOTOGRAPHY

Author(s)
SAQIB MAJEED University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Pakistan
SALEEM IQBAL University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Pakistan
ADNAN AHMED Department of Computer Systems Engineering, Quaid-e-Awam University of Engineering, Science and Technology,Nawabshah, Pakistan
KULSOOM AZAD University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Pakistan
KASHIF SATTAR University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Pakistan
Abstract
The retrieval of images using semantic concepts is challenging and essential issue in watchword based search. The focus has been shifted from low-level feature extraction to human semantics in order to enhance the precision of content based image recovery framework. It is done to decrease the semantic gap between visual components and affluence of human semantics. This research provides an ontology-driven approach to train the system by modeling the human cognition that also conquers the constraints of a label based retrieval. In the proposed work, a properly characterised philosophy framework is used to drive image annotations that enable semantic retrieval of aerial photography. The concept of image semantics is exploited for the classifi­cation of vegetation and also to determine the qualitative semantics by using Allen’s qualitative relations. Psychophysical evaluation is used to assess the eectiveness of the proposed approach. The outcomes of the different experiments are relatively favorable in terms of accuracy of relevant image retrieval.
Publication Details
Page(s) 32-37
DOI DOI not available
Published Journal: Quaid-e-Awam University Research Journal of Engineering, Science and Technology, Volume: 15, Issue: 2, Year: 2016

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Keywords
Vegetation Classi cation, Qualitative Semantics, Aerial Photography, Semantic Image Retrieval
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