Abstract: Among the many handwritten character recognition algorithms that have been proposed, few of them use models which are able to simulate handwriting. This can be explained by the fact that simulations require the estimation of strokes starting form statistic imags of letters, while crossing and overlapping strokes make this estimation difficult. In this paper an algorithm to extract overlapping strokes that optimizes the reconstruction of crossings of the image is describes, and a stochastic model of off-line handwritten letter deformation for handwritten letter recognition is presented. !9
展开▼
