Segmentation by minimum length encoding

Daniel Keren, Ruth Marcus, Michael Werman, Shmuel Peleg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A digitized waveform is approximated by segments whose total description length is minimal for a given error bound. This approximation can be computed efficiently and can be used for segmentation. Some applications involving the use of one-dimensional methods to segment two-dimensional gray-scale and range images are shown.

Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherPubl by IEEE
Pages681-683
Number of pages3
ISBN (Print)0818620625
StatePublished - 1990
Externally publishedYes
EventProceedings of the 10th International Conference on Pattern Recognition - Atlantic City, NJ, USA
Duration: 16 Jun 199021 Jun 1990

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume1

Conference

ConferenceProceedings of the 10th International Conference on Pattern Recognition
CityAtlantic City, NJ, USA
Period16/06/9021/06/90

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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