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

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dc.contributor.authorRajpal, Navin-
dc.contributor.authorChaudhury, Santanu-
dc.contributor.authorBanerjee, Subhashis-
dc.identifier.citationPattern Recognition, 32(10), 1737-1749en
dc.description.abstractIn 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.en
dc.format.extent630762 bytes-
dc.subjectObject recognitionen
dc.subjectInvariant indexingen
dc.subjectNeural networksen
dc.subjectContour segmentsen
dc.titleRecognition of partially occluded objects using neural network based indexingen
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