Abstract
This paper presents an original system for the automatic detection of droppers in catenary staves. Based on a top-down approach, our system exploits a priori knowledge that are used to perform a reliable extraction of droppers. Experiments conducted on a significant database of real catenary stave images show some promising results on this very challenging machine vision application. © 2009 Springer Berlin Heidelberg.
Cite
CITATION STYLE
Petitjean, C., Heutte, L., Kouadio, R., & Delcourt, V. (2009). A top-down approach for automatic dropper extraction in catenary scenes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5524 LNCS, pp. 225–232). https://doi.org/10.1007/978-3-642-02172-5_30
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