Two-dimensional linear predictive analysis of arbitrarily-shaped regions

Maragos, P; Mersereau, R; Schafer, R

dc.contributor.author	Maragos, P	en
dc.contributor.author	Mersereau, R	en
dc.contributor.author	Schafer, R	en
dc.date.accessioned	2014-03-01T02:47:34Z
dc.date.available	2014-03-01T02:47:34Z
dc.date.issued	1983	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/33233
dc.subject	Distance Measure	en
dc.subject	Image Segmentation	en
dc.subject	Linear Predictive	en
dc.title	Two-dimensional linear predictive analysis of arbitrarily-shaped regions	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICASSP.1983.1172205	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICASSP.1983.1172205	en
heal.publicationDate	1983	en
heal.abstract	This paper is concerned with the use of 2-D linear prediction for image segmentation. It begins with a brief summary of the mathematics involved in 2-D linear predictive analysis of arbitrarily-shaped regions. Then, it introduces a 2-D LPC distance measure based on the error residual of 2-D linear prediction. Finally, it describes how the above results can be applied to	en
heal.journalName	International Conference on Acoustics, Speech, and Signal Processing	en
dc.identifier.doi	10.1109/ICASSP.1983.1172205	en