A soft approach for feature selection and recognition of outdoor natural images

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dc.contributor.author Dhariwal, Tarun
dc.contributor.author Agarwal, Arun
dc.contributor.author Rao, C. R.
dc.date.accessioned 2022-03-27T05:52:13Z
dc.date.available 2022-03-27T05:52:13Z
dc.date.issued 2013-11-22
dc.description.abstract For applications like scene classification, CBIR, automated tagging, motion of a robot in a real world using vision system, understanding the images captured by the visual sensors is quite important. For such high level processing task it is mandatory to have a set of good feature. This paper discusses the application of fuzzy rough set theory for selecting a set of best features from the feature set of regions which are segmented out from outdoor natural images using a segmentation algorithm. The paper explains a complete system i.e. from feature selection/region labelling based on fuzzy rough set theory. The images used in experiments are color-texture natural images taken from the campus of University of Hyderabad. © 2013 IEEE.
dc.identifier.citation IEEE International Conference on Fuzzy Systems
dc.identifier.issn 10987584
dc.identifier.uri 10.1109/FUZZ-IEEE.2013.6622528
dc.identifier.uri http://ieeexplore.ieee.org/document/6622528/
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/8500
dc.subject Classification
dc.subject Feature selection
dc.subject Fuzzy decision reduct
dc.subject Recognition
dc.subject Rough set theory
dc.subject Segmentation
dc.title A soft approach for feature selection and recognition of outdoor natural images
dc.type Conference Proceeding. Conference Paper
dspace.entity.type
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