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Unsupervised classifying land development in high resolution multi-spectral satellite photos and application for facial features extraction

  • Uri Lipowezky
  • , Yoram Furth
  • , Ephraim Luson

Research output: Contribution to conferencePaperpeer-review

2 Scopus citations

Abstract

A novel method of unsupervised detection of the different types of land development using multi-spectral IKONOS satellite photos is proposed. The method is based on image decomposition into two clusters: the type of land development in quest and the rest of the image, using optimal (the most informative) combination of color and spatial homogeneity indicators. Experimental study of the proposed technique shows fast and reliable deciphering of the vegetation, bare soils, water, roads and residential areas. The results of this preliminary classification are used for accurate decipherment of terrain details using high resolution BW IKONOS photo, which comes along with the multi-spectral one. It is shown that proposed technique is suitable for facial features extraction as well. Fast and reliable detection of human skin, eyes, mouth, hair face triangle and oval is obtained on different subjects.

Original languageEnglish
Pages428-431
Number of pages4
StatePublished - 1 Dec 2004
Externally publishedYes
Event2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings - Tel-Aviv, Israel
Duration: 6 Sep 20047 Sep 2004

Conference

Conference2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings
Country/TerritoryIsrael
CityTel-Aviv
Period6/09/047/09/04

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

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