Affine invariant representation and classification of object contours for image and video retrieval

Avrithis, Y; Xirouhakis, Y; Kollias, S

dc.contributor.author	Avrithis, Y	en
dc.contributor.author	Xirouhakis, Y	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T01:48:31Z
dc.date.available	2014-03-01T01:48:31Z
dc.date.issued	1999	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25496
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-4944220656&partnerID=40&md5=ee9c3111dce7c8ff924b2a9ab8eac21c	en
dc.subject	Affine-invariant representation	en
dc.subject	Image and video retrieval and classification	en
dc.subject	Object contours	en
dc.subject.other	Computer simulation	en
dc.subject.other	Curve fitting	en
dc.subject.other	Database systems	en
dc.subject.other	Fourier transforms	en
dc.subject.other	Mathematical models	en
dc.subject.other	Textures	en
dc.subject.other	Video signal processing	en
dc.subject.other	Affine-invariant representation	en
dc.subject.other	Object contours	en
dc.subject.other	Video classification	en
dc.subject.other	Video retrieval	en
dc.subject.other	Image retrieval	en
dc.title	Affine invariant representation and classification of object contours for image and video retrieval	en
heal.type	journalArticle	en
heal.publicationDate	1999	en
heal.abstract	Recent literature comprises a large number of papers on the query and retrieval of visual information based on its content. At the same time, a number of prototype systems have been implemented enabling searching through on-line image databases--and still image retrieval. However, it has been often pointed out that meaningful/semantic information should be extracted from visual information in order to improve the efficiency and functionality of a content-based retrieval tool. In this context, present work focuses on the extraction of objects from images and video clips and modeling of the resulting object contours using B-splines. Affine-invariant curve representation is obtained through Normalized Fourier descriptors (NFD), curve moments, as well as a novel curve normalization algorithm that leads to major preservation of object shape information. A neural network approach is employed for supervised classification of video objects into prototype object classes. Experiments on several real-life and simulated video sequences are included to evaluate the classification results for all affine-invariant representations used.	en
heal.publisher	World Scientific and Engineering Academy and Society	en
heal.journalName	Computational Intelligence and Applications	en
dc.identifier.spage	342	en
dc.identifier.epage	347	en