Summary
This paper presents a segmentation technique to handwritten word recognition. This technique implements an algorithm based on an analytical approach. It uses a letter sweeping procedure with a step equal to the Euclidean distance between an established reference index and the entity (the alphabet letter). Then a dissociation of this entity is achieved when this distance will reach a rate of 80%. Our experience about this segmentation technique gives a rate of 81.05% of recognition. A neural multilayer perceptron classifier confirms the extracted segment. This procedure is successively repeated from the beginning until the end of the word. A concatenation technique is finally used to the word reconstitution.
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Extract
A Segmentation Method to Handwritten Word Recognition
1. Introduction
The pattern recognition is an artificial intelligence domain which concerns various problems of objects identification. Thus, the pattern recognition deals with manmachine communication framework. As an interesting application of pattern recognition is the handwritten word recognition. The aim is to transform a handwritten text into a printed text [8] . The handwritten word recognition is not evident because the letters have an infinity representation form. Today, there are several commercialized applications of the handwritten word recognition as the automatic mail sorting, the automatic treatment of administrative files, the search forms and the bank checks examination. These ...See the full content of this document
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