DSpace
 

EPrints@IIT Delhi >
Faculty Research Publicatons  >
Computer Science and Engineering >

Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/707

Title: Recognition of partially occluded objects using neural network based indexing
Authors: Rajpal, Navin
Chaudhury, Santanu
Banerjee, Subhashis
Keywords: Object recognition
Invariant indexing
Neural networks
Hypothesize-and-test
Contour segments
Issue Date: 1999
Citation: Pattern Recognition, 32(10), 1737-1749
Abstract: In this paper, a new neural network based indexing scheme has been proposed for recognition of planar shapes. Local contour segment-based-invariants have been used for indexing. Object contours have been obtained using a new algorithm which combines advantages of region growing and edge detection. Neighbourhood constraints have been applied on the results of indexing for combining hypotheses generated through the indexing scheme. Composite hypotheses have been verified using a distance transform based algorithm. Experimental results, on real images of varying complexity of a reasonably large database of objects have established the robustness of the method.
URI: http://eprint.iitd.ac.in/dspace/handle/2074/707
Appears in Collections:Computer Science and Engineering

Files in This Item:

File Description SizeFormat
rajpalrec1999.pdf615.98 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback