A Top-Down Approach for Automatic Dropper Extraction in Catenary Scenes

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.