arXiv subjects
Publications and source records attributed to Ioan Snep.
This paper presents an original solution for flexible hand-written text division into rows. Unlike the standard procedure, the proposed method avoids the isolated characters extensions amputation and reduces the recognition error rate in the final stage.
The goal of this paper is to present the implementation of a Radial Basis Function neural network with built-in knowledge to recognize hand-written characters. The neural network includes in its architecture gates controlled by an attraction/repulsion system of coefficients. These coefficients are derived from a preprocessing stage which groups the characters according to their ascendant, central, or descendent components. The neural network is trained using data from invariant moment functions. Results are compared with those obtained using a K nearest neighbor method on the same moment data.