A segmentation method to handwritten word recognition
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 stop 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 multi-layer 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.
segmentation handwritten word pattern recognition neural networks