On the classification of image features Venkatesh, Svetha and Owens, Robyn 1990, On the classification of image features, Pattern recognition letters, vol. 11, no. 5, pp. 339-349, doi: 10.1016/0167-8655(90)90043-2. Attached Files Name Description MIMEType Size Downloads Title On the classification of image features Author(s) Venkatesh, Svetha orcid.org/0000-0001-8675-6631 Owens, Robyn Journal name Pattern recognition letters Volume number 11 Issue number 5 Start page 339 End page 349 Total pages 11 Publisher Elsevier BV Place of publication Amsterdam, Netherlands Publication date 1990-05 ISSN 0167-8655 1872-7344 Keyword(s) edge classification edge detection Hilbert transform local energy Summary While the primary purpose of edge detection schemes is to be able to produce an edge map of a given image, the ability to distinguish between different feature types is also of importance. In this paper we examine feature classification based on local energy detection and show that local energy measures are intrinsically capable of making this classification because of the use of odd and even filters. The advantage of feature classification is that it allows for the elimination of certain feature types from the edge map, thus simplifying the task of object recognition. Language eng DOI 10.1016/0167-8655(90)90043-2 Field of Research 080109 Pattern Recognition and Data Mining Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture) HERDC Research category C1.1 Refereed article in a scholarly journal Copyright notice ©1990, Published by Elsevier B.V. Persistent URL http://hdl.handle.net/10536/DRO/DU:30044244 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 05 Apr 2012, 16:00:29 EST Wed, 18 Apr 2012, 15:40:05 EST Wed, 18 Apr 2012, 15:40:48 EST Mon, 30 Apr 2012, 09:16:01 EST Fri, 13 Jun 2014, 13:41:49 EST Filtered Full Citation counts:   Cited 77 times in TR Web of Science Cited 105 times in Scopus Search Google Scholar Access Statistics: 612 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Thu, 05 Apr 2012, 16:00:29 EST

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