Perceptually based techniques for image segmentation and semantic classification

Thrasyvoulos N. Pappas; Junqing Chen; Dejan Depalov

doi:10.1109/MCOM.2007.284537

Perceptually based techniques for image segmentation and semantic classification

Thrasyvoulos N. Pappas^*, Junqing Chen, Dejan Depalov

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	44-51
Number of pages	8
Journal	IEEE Communications Magazine
Volume	45
Issue number	1
DOIs	https://doi.org/10.1109/MCOM.2007.284537
State	Published - Jan 2007

Funding

This work was supported by the National Science Foundation (NSF) under Grant no. CCR-0209006, and the Defense Intelligence Agency (DIA) under DIA/NSF Grant no. IIS-0515929. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF or DIA. This work was also supported by the Motorola Center for Telecommunications at Northwestern University. Special thanks to Aleksandra Mojsilovic and Bernice Rogowitz of IBM T. J. Watson Research Center and Dongge Li and Bhavan Gandhi of Motorola Labs for many discussions and suggestions on various aspects of the work that led to this article.

ASJC Scopus subject areas

Computer Science Applications
Computer Networks and Communications
Electrical and Electronic Engineering

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10.1109/MCOM.2007.284537

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abstract = "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.",

author = "Pappas, {Thrasyvoulos N.} and Junqing Chen and Dejan Depalov",

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Perceptually based techniques for image segmentation and semantic classification

Abstract

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ASJC Scopus subject areas

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