IEEE Transactions on Pattern Analysis and Machine Intelligence
Holistic Verification of Handwritten Phrases
IEEE Transactions on Pattern Analysis and Machine Intelligence
On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Role of Holistic Paradigms in Handwritten Word Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Omnifont and Unlimited-Vocabulary OCR for English and Arabic
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Optical Character Recognition Without Segmentation
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
An automatic reading system for handwritten numeral amounts on French checks
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
A hybrid radial basis function network/hidden Markov model handwritten word recognition system
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
An Approach to Word Image Matching Based on Weighted Hausforff Distance
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Robust Word Recognition for Museum Archive Card Indexing
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Style-Consistency in Isogenous Patterns
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Computerising Natural History Card Archives
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Fast Lexicon-Based Word Recognition in Noisy Index Card Images
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
A Study on Top-down Word Image Generation for Handwritten Word Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
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This paper describes a new top-down word image generation model for word recognition. This model can generate a word image with a likelihood based on linguistic knowledge, segmentation and character image. In the recognition process, first, the model generates the word image which approximates an input image best for each of a dictionary of possible words. Next, the model calculates the distance value between the input image and each generated word image. Thus, the proposed method is a type of holistic word recognition method. The effectiveness of the proposed method was evaluated in an experiment using type-written museum archive card images. The difference between a non-holistic method and the proposed method is shown by the evaluation. The small errors accumulate in non-holistic methods during the process carried out, because the non-holistic methods can't cover the whole word image but only part images extracted by segmentation, and the non-holistic method can't eliminate the blackpixels intruding in the recognition window from neighboring characters. In the proposed method, we can expect that no such errors will accumulate. Results show that a recognition rate of 99.8% was obtained, compared with only 89.4% for a recently published comparator algorithm.