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Towards Segmentation from Multiple Cues: Symmetry and Color

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Multi-Image Analysis

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2032))

Abstract

Towards segmentation from multiple cues, this paper demonstrates the combined use of color and symmetry for detecting regions of interest (ROI), using the detection of man-made wooden objects and the detection of faces as working examples. A functional that unifies color compatibility and color-symmetry within elliptic supports is defined. Using this functional, the ROI detection problem becomes a five-dimensional global optimization problem. Exhaustive-search is inapplicable due its prohibitive computational cost. Genetic search converges rapidly and provides good results. The added value obtained by combining color and symmetry is demonstrated.

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Authors and Affiliations

  1. Dept. of Electrical Engineering-Systems, Tel Aviv University, Tel Aviv, 69978, Israel

    Roy Shor & Nahum Kiryati

Authors
  1. Roy Shor
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  2. Nahum Kiryati
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Editor information

Editors and Affiliations

  1. Center for image Technology and Robotics (CITR Tamaki), Auckland, New Zealand

    Reinhard Klette  & Georgy Gimel’farb  & 

  2. 2039 Beckman Institute, University of Illinois, 405 N. Mathews, Urbana, IL, 61801, USA

    Thomas Huang

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© 2001 Springer-Verlag Berlin Heidelberg

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Shor, R., Kiryati, N. (2001). Towards Segmentation from Multiple Cues: Symmetry and Color. In: Klette, R., Gimel’farb, G., Huang, T. (eds) Multi-Image Analysis. Lecture Notes in Computer Science, vol 2032. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45134-X_11

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  • DOI: https://doi.org/10.1007/3-540-45134-X_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42122-1

  • Online ISBN: 978-3-540-45134-1

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