A Contour-Based Part Segmentation Algorithm

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A Contour-Based Part Segmentation Algorithm

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dc.contributor.author Bennamoun, M
dc.contributor.author Boashash, B
dc.date.accessioned 2012-05-07T16:08:37Z
dc.date.available 2012-05-07T16:08:37Z
dc.date.issued 1997-08
dc.identifier.citation IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E80-A, No. 8, pp. 1516-1421, August, 1997 en_US
dc.identifier.issn 0916-8508
dc.identifier.uri http://hdl.handle.net/10576/10823
dc.description This paper presents a part-Segmentation algorithm to decompose an object described by its contour into convex parts. (Other relevant details may be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). en_US
dc.description.abstract Within the framework of a previously proposed vision system, a new part-segmentation algorithm, that breaks an object defined by its contour into its constituent parts, is presented. The contour is assumed to be obtained using an edge detector. This decomposition is achieved in two stages. The first stage is a preprocessing step which consists of extracting the convex dominant points (CDPs) of the contour. For this aim, we present a new technique which relaxes the compromise that exists in most classical methods for the selection of the width of the Gaussian filter. In the subsequent stage, the extracted CDPs are used to break the object into convex parts. This is performed as follows: among all the points of the contour only the CDPs are moved along their normals nutil they touch another moving CDP or a point on the contour. The results show that this part-segmentation algorithm is invariant to transformations such as rotation, scaling and shift in position of the object, which is very important for object recognition. The algorithm has been tested on many object contours, with and without noise and the advantages of the algorithm are listed in this paper. Our results are visually similar to a human intuitive decomposition of objects into their parts. en_US
dc.language.iso en en_US
dc.publisher IEICE en_US
dc.subject Pattern recognition en_US
dc.subject vision systems en_US
dc.subject part segmentation en_US
dc.subject parameter selection en_US
dc.subject edge detection en_US
dc.subject dominant point en_US
dc.subject Convex point en_US
dc.subject Gaussian filter en_US
dc.subject invariance en_US
dc.title A Contour-Based Part Segmentation Algorithm en_US
dc.type Article en_US

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