SITT - A Simple Robust Scaleinvariant Text Feature Detector
Marco Block, Marte Ramirez Ortegon, Alexander Seibert, Jan Kretzschmar, Raul Rojas – 2007
In this paper we present SITT, a simple robust scaleinvariant text feature detector for document mosaicing. Digital image stitching has been studied for several decades. SIFT-Features in combination with RANSAC algorithm are established to produce good panoramas. The main problem of realtime text document stitching is the size of the feature set created by SIFT-Features. We introduce SITT-Features to solve this problem. Our experiments denote that for document images SITT-Features produce faster good results than SIFT-Features.