Fusion of Multi-view Tissue Classification Based on Wound 3D Model

  • Hazem Wannous
  • Yves Lucas
  • Sylvie Treuillet
  • Benjamin Albouy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5259)


Region classification from a single image is no more reliable when the labeling must be applied on a 3D surface. Depending on camera viewpoint and surface curvature, lighting variations and perspective effects alter colorimetric analysis and area measurements. This problem can be overcome if a 3D model of the object of interest is available. This general approach has been evaluated for the design of a complete wound assessment tool using a simple free handled digital camera. Clinical tests demonstrate that multi view classification results in enhanced tissue labeling and more precise measurements, a significant step toward accurate monitoring of the healing process.


Fusion Algorithm Stereo Pair Dominant Class Tissue Class Tissue Classification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Hazem Wannous
    • 1
  • Yves Lucas
    • 2
  • Sylvie Treuillet
    • 3
  • Benjamin Albouy
    • 4
  1. 1.Institut PRISME, ENSI de BourgesBourgesFrance
  2. 2.Institut PRISMEIUT Bourges Université d’Orléans av. de LattreBourgesFrance
  3. 3.Institut PRISMEEcole Polytechnique Université d’OrléansOrléansFrance
  4. 4.LAICIUT Le Puy en Velay, Université Clermont ILe Puy en VelayFrance

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