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

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

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dc.contributor.author Bennamoun, M
dc.contributor.author Boashash, Boualem
dc.date.accessioned 2011-07-24T06:41:26Z
dc.date.available 2011-07-24T06:41:26Z
dc.date.issued 1997-12
dc.identifier.citation IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics,Volume : 27 , Issue:6 On page(s): 893 en_US
dc.identifier.issn 1083-4419
dc.identifier.uri http://hdl.handle.net/10576/10717
dc.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
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Cost function en_US
dc.subject Detectors en_US
dc.subject Filters en_US
dc.subject Image edge detection en_US
dc.subject Machine vision en_US
dc.subject Object detection en_US
dc.subject Shape en_US
dc.subject Signal processing algorithms en_US
dc.subject Two dimensional display en_US
dc.subject 2D super-quadrics en_US
dc.subject Gaussian filter en_US
dc.subject automatic object recognition en_US
dc.subject best-fit cost function en_US
dc.subject computer vision en_US
dc.subject contour extraction en_US
dc.subject convex point en_US
dc.subject differential edge detector en_US
dc.subject dominant point en_US
dc.subject object recognition en_US
dc.subject parameter selection en_US
dc.subject part segmentation en_US
dc.subject structural-description en_US
dc.subject invariance en_US
dc.subject modeling en_US
dc.subject part isolation en_US
dc.subject Pattern recognition en_US
dc.subject superquadrics en_US
dc.subject vision systems en_US
dc.title A structural-description-based vision system for automatic object recognition en_US
dc.type Article en_US

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