A segmentation and recognition strategy for handwritten phrases

A segmentation and recognition method for handwritten phrases, such as street names, is presented in this paper. Some of the challenges posed by the problem are: (1) identifying correct word gaps from character gaps and (2) minimization of computational complexity during the recognition of potential...

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Bibliographic Details
Published inProceedings of 13th International Conference on Pattern Recognition Vol. 4; pp. 510 - 514 vol.4
Main Authors Gyeonghwan Kim, Govindaraju, V., Srihari, S.N.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Character recognition
Computational complexity
Engines
Handwriting recognition
Image segmentation
Neural networks
Text analysis
Text recognition
Venus
Writing
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ISBN9780818672828
081867282X
ISSN1051-4651
DOI10.1109/ICPR.1996.547617

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Summary:A segmentation and recognition method for handwritten phrases, such as street names, is presented in this paper. Some of the challenges posed by the problem are: (1) identifying correct word gaps from character gaps and (2) minimization of computational complexity during the recognition of potential words. A trainable word segmentation scheme using a neural network is introduced. The network learns the type of spacing (including size) that one should expect between different pairs of characters in handwritten text. The concept of variable duration, which is obtained during the training phase of a word recognition engine we have developed, is expanded to reduce the computational complexity which has been a serious concern in this type of application.
ISBN:9780818672828
081867282X
ISSN:1051-4651
DOI:10.1109/ICPR.1996.547617