Online Recognition of Chinese Characters: The State-of-the-Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ontology Guided Access to Document Images
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Application of information retrieval techniques to single writer documents
Pattern Recognition Letters
Retrieval of online handwriting by synthesis and matching
Pattern Recognition
Versatile search of scanned Arabic handwriting
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
Ranking fusion methods applied to on-line handwriting information retrieval
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Hi-index | 0.00 |
This paper investigates the use of both typed and handwritten queries to retrieve handwritten documents. The recognition-based approach reported here is novel in that it expands documents in a fashion analogous to query expansion: Individual documents are expanded using N-best lists which embody additional statistical information from a Hidden Markov Model (HMM) based handwriting recognizer used to transcribe each of the handwritten documents.This additional information enables the retrieval methods to be robust to machine transcription errors, retrieving documents which otherwise would be unretrievable. Cross-writer experiments on a database of 10985 words in 108 documents from 108 writers, and within-writer experiments in a probabilistic framework, on a database of 537724 words in 3342 documents from 43 writers, indicate that significant improvements in retrieval performance can be achieved. The second database is the largest database of on-line handwritten documents known to us.