Perceptually based techniques for image segmentation and semantic classification

Thrasyvoulos N. Pappas*, Junqing Chen, Dejan Depalov

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


We present a new approach for semantic image analysis that combines knowledge of human perception with an understanding of signal characteristics to segment natural scenes into perceptually uniform regions, and then uses the region statistics to extract semantic information. Applications include content-based image retrieval and region of interest extraction for efficient compression/transmission over heterogeneous networks.

Original languageEnglish (US)
Pages (from-to)44-51
Number of pages8
JournalIEEE Communications Magazine
Issue number1
StatePublished - Jan 2007

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering


Dive into the research topics of 'Perceptually based techniques for image segmentation and semantic classification'. Together they form a unique fingerprint.

Cite this