Object Representation and Matching Based on Skeletons and Curves

Studien zur Mustererkennung , Bd. 40

Christian Feinen

ISBN 978-3-8325-4257-3
260 pages, year of publication: 2016
price: 50.50 €
Object Representation and Matching Based on Skeletons and Curves
This thesis is dedicated to the problem of object recognition in the three-dimensional space. Instead of using exclusively the information typically transported by a two-dimensional image, the concept of this work additionally incorporates the third dimension, namely the depth. The depth data itself is captured by sensors capable of measuring the distance from the device's position to those objects residing inside its field of view. The actual recognition process is implemented in analogy to the Path Similarity Skeleton Graph Matching (PSSGM).

Basically, this method represents a 2D object by its skeleton and uses the idea of shortest paths to describe it. Finally, the similarity between two objects is calculated based on the Hungarian method. The contribution of the current work maps this approach into the three-dimensional space and applies it to 3D objects. While one of the experiments aims at the recognition of 3D chairs and tables, another one is devoted to the registration of fully segmented vascular structures. Excellent and promising recognition results are achieved in challenging evaluation setups showing that the 3D version of the PSSGM has the potential to solve complex recognition tasks.

cover cover cover cover cover cover cover cover cover
Table of contents (PDF)


  • Pattern Recognition
  • 2D/3D Object Recognition
  • 2D/3D Object Representation
  • Skeletons and Curves
  • Graph-Based Object Matching


50.50 €
in stock

40.00 €
60.50 €
64.50 €

(D) = Within Germany
(W) = Abroad

*You can purchase the eBook (PDF) alone or combined with the printed book (eBundle). In both cases we use the payment service of PayPal for charging you - nevertheless it is not necessary to have a PayPal-account. With purchasing the eBook or eBundle you accept our licence for eBooks.

For multi-user or campus licences (MyLibrary) please fill in the form or write an email to