In this paper, we present a mathematical model for evaluating codes and primitives in optical character recognition. The model is based on code efficiency, calculated from its average length and its transmitted information. This efficiency is obtained from entropies and conditional entropies which are estimated from probabilities of character recognition depending on the issued codes. This method is used to evaluate two sets of primitives in numeral recognition. Then, we propose a method of constructing binary decision trees for the recognition of handwritten numerals. This method is based on the mathematical model previously stated, which is used to process the transmitted information about the primitives. We demonstrate the performance of our system with experiments using real data.
Evaluation of codes and primitives: recognition of unconstrained handwritten numerals
Proceedings of 3rd International Conference on Document Analysis and Recognition ; 1 ; 104-107 vol.1
01.01.1995
425150 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Evaluation of Codes and Primitives: Recognition of Unconstrained Handwritten Numerals
British Library Conference Proceedings | 1995
|A Multi-Layer Classifier for Recognition of Unconstrained Handwritten Numerals
British Library Conference Proceedings | 1995
|British Library Online Contents | 2004
|British Library Conference Proceedings | 2002
|