Recognition of Cursive Roman Handwriting - Past, Present and Future
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Features for Word Spotting in Historical Manuscripts
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
A Scale Space Approach for Automatically Segmenting Words from Historical Handwritten Documents
IEEE Transactions on Pattern Analysis and Machine Intelligence
Application of information retrieval techniques to single writer documents
Pattern Recognition Letters
Holistic approach for classifying and retrieving personal Arabic handwritten documents
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
Word Spotting in Archive Documents Using Shape Contexts
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Classification of personal Arabic handwritten documents
WSEAS Transactions on Information Science and Applications
Expert Systems with Applications: An International Journal
Handwritten word-spotting using hidden Markov models and universal vocabularies
Pattern Recognition
Integrated Computer-Aided Engineering
User-assisted alignment of Arabic historical manuscripts
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
Transcription alignment of Latin manuscripts using hidden Markov models
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
Using relevance feedback to learn both the distance measure and the query in multimedia databases
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Aligning transcripts to automatically segmented handwritten manuscripts
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Hi-index | 0.00 |
There is a large number of scanned historical documents that need to be indexed for archival and retrieval purposes. A visual word spotting scheme that would serve these purposes is a challenging task even when the transcription of the document image is available. We propose a framework for mapping each word in the transcript to the associated word image in the document. Coarse word mapping based on document constraints is used for lexicon reduction. Then, word mappings are refined using word recognition results by a dynamic programming algorithm that finds the best match while satisfying the constraints.