Generic Shape Classification for Retrieval

  • Manuel J. Fonseca
  • Alfredo Ferreira
  • Joaquim A. Jorge
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3926)


We present a shape classification technique for structural content–based retrieval of two-dimensional vector drawings. Our method has two distinguishing features. For one, it relies on explicit hierarchical descriptions of drawing structure by means of spatial relationships and shape characterization. However, unlike other approaches which attempt rigid shape classification, our method relies on estimating the likeness of a given shape to a restricted set of simple forms. It yields for a given shape, a feature vector describing its geometric properties, which is invariant to scale, rotation and translation. This provides the advantage of being able to characterize arbitrary two–dimensional shapes with few restrictions. Moreover, our technique seemingly works well when compared to established methods for two dimensional shapes.


Feature Vector Image Retrieval Delaunay Triangulation Zernike Moment Fourier Descriptor 
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 2006

Authors and Affiliations

  • Manuel J. Fonseca
    • 1
  • Alfredo Ferreira
    • 1
  • Joaquim A. Jorge
    • 1
  1. 1.Department of Information Systems and Computer ScienceINESC-ID/IST/Technical University of LisbonPortugal

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