Expanded Dempster-Shafer reasoning technique for image feature integration and object recognition

Qiuming Zhu, Yinghua Huang, Matt G. Payne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Integration of information from multiple sources has been one of the key steps to the success of general vision systems. It is also an essential problem to the development of color image understanding algorithms that make full use of the multichannel color data for object recognition. This paper presents a feature integration system characterized by a hybrid combination of a statistic-based reasoning technique and a symbolic logic-based inference method. A competitive evidence enhancement scheme is used in the process to fuse information from multiple sources. The scheme expands the Dempster-Shafer's function of combination and improves the reliability of the object recognition. When applied to integrate the object features extracted from the multiple spectra of the color images, the system alleviates the drawback of traditional Baysian classification system.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherPubl by Int Soc for Optical Engineering
Pages36-47
Number of pages12
ISBN (Print)0819409391
StatePublished - 1992
EventNeural and Stochastic Methods in Image and Signal Processing - San Diego, CA, USA
Duration: Jul 20 1992Jul 23 1992

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume1766
ISSN (Print)0277-786X

Other

OtherNeural and Stochastic Methods in Image and Signal Processing
CitySan Diego, CA, USA
Period7/20/927/23/92

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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    Zhu, Q., Huang, Y., & Payne, M. G. (1992). Expanded Dempster-Shafer reasoning technique for image feature integration and object recognition. In Proceedings of SPIE - The International Society for Optical Engineering (pp. 36-47). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 1766). Publ by Int Soc for Optical Engineering.