IEEE Transactions on Pattern Analysis and Machine Intelligence
A Lexicon Driven Approach to Handwritten Word Recognition for Real-Time Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Large-Scale Simulation Studies in Image Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
An HMM-Based Approach for Off-Line Unconstrained Handwritten Word Modeling and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of Lexicon Density in Evaluating Word Recognizers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Influence of Word Length on Handwriting Recognition
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
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
Building Skeletal Graphs for Structural Feature Extraction on Handwriting Images
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
IEEE Transactions on Image Processing
A Human Interactive Proof Algorithm Using Handwriting Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
A Lexicon Reduction Strategy in the Context of Handwritten Medical Forms
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Improving word-recognizers using an interactive lexicon with active and passive words
Proceedings of the 13th international conference on Intelligent user interfaces
Leveraging cognitive factors in securing WWW with CAPTCHA
WebApps'10 Proceedings of the 2010 USENIX conference on Web application development
Exploring similarity measures for biometric databases
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Visual CAPTCHA with handwritten image analysis
HIP'05 Proceedings of the Second international conference on Human Interactive Proofs
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The performance of any word recognizer depends on the lexicon presented. Usually, large lexicons or lexicons containing similar entries pose difficulty for recognizers. However, the literature lacks any quantitative methodology of capturing the precise dependence between word recognizers and lexicons. This paper presents a performance model that views word recognition as a function of character recognition and statistically "discovers" the relation between a word recognizer and the lexicon. It uses model parameters that capture a recognizer's ability of distinguishing characters (of the alphabet) and its sensitivity to lexicon size. These parameters are determined by a multiple regression model which is derived from the performance model. Such a model is very useful in comparing word recognizers by predicting their performance based on the lexicon presented. We demonstrate the performance model with extensive experiments on five different word recognizers, thousands of images, and tens of lexicons. The results show that the model is a good fit not only on the training data but also in predicting the recognizers' performance on testing data.