Publikation
Part-Based Recognition of Handwritten Characters
Seiichi Uchida; Marcus Liwicki
In: Proceedings of the 12th International Conference on Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition (ICFHR-10), November 16-18, Kolkata, India, Pages 545-550, 2010.
Zusammenfassung
In the part-based recognition method proposed in
this paper, a handwritten character image is represented
by just a set of local parts. Then, each local
part of the input pattern is recognized by a nearestneighbor
classifier. Finally, the category of the input
pattern is determined by aggregating the local recognition
results. This approach is opposed to conventional
character recognition approaches which try to
benefit from the global structure information as much
as possible. Despite a pessimistic expectation, we have
reached recognition rates much higher than 90% for a
digit recognition task. In this paper we provide a detailed
analysis in order to understand the results and
find the merits of the local approach.