A structural-description-based vision system for automatic object recognition

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contributor.author Bennamoun, M en_US
contributor.author Boashash, Boualem en_US
date.accessioned 2011-07-24T06:41:26Z en_US
date.accessioned 2015-02-01T08:24:37Z
date.available 2011-07-24T06:41:26Z en_US
date.available 2015-02-01T08:24:37Z
date.issued 1997-12 en_US
identifier.citation IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics,Volume : 27 , Issue:6 On page(s): 893 en_US
identifier.issn 1083-4419 en_US
identifier.uri http://hdl.handle.net/10576/10717 en_US
description.abstract This paper presents the results of the integration of a proposed part-segmentation-based vision system. The first stage of this system extracts the contour of the object using a hybrid first- and second-order differential edge detector. The object defined by its contour is then decomposed into its constituent parts using the part segmentation algorithm given by Bennamoun (1994). These parts are then isolated and modeled with 2D superquadrics. The parameters of the models are obtained by the minimization of a best-fit cost function. The object is then represented by its structural description which is a set of data structures whose predicates represent the constituent parts of the object and whose arguments represent the spatial relationship between these parts. This representation allows the recognition of objects independently of their positions, orientations, or sizes. It is also insensitive to objects with partially missing parts. In this paper, examples illustrating the acquired images of objects, the extraction of their contours, the isolation of the parts, and their fitting with 2D superquadrics are reported. The reconstruction of objects from their structural description is illustrated and improvements are suggested. en_US
language.iso en en_US
publisher IEEE en_US
subject Cost function en_US
subject Detectors en_US
subject Filters en_US
subject Image edge detection en_US
subject Machine vision en_US
subject Object detection en_US
subject Shape en_US
subject Signal processing algorithms en_US
subject Two dimensional display en_US
subject 2D super-quadrics en_US
subject Gaussian filter en_US
subject automatic object recognition en_US
subject best-fit cost function en_US
subject computer vision en_US
subject contour extraction en_US
subject convex point en_US
subject differential edge detector en_US
subject dominant point en_US
subject object recognition en_US
subject parameter selection en_US
subject part segmentation en_US
subject structural-description en_US
subject invariance en_US
subject modeling en_US
subject part isolation en_US
subject Pattern recognition en_US
subject superquadrics en_US
subject vision systems en_US
title A structural-description-based vision system for automatic object recognition en_US
type Article en_US


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