| Hi-index | 0.01 |
This paper proposes a model-dependent pattern normalization method that employs an elastic membrane model to absorb pattern deformation in handwritten character patterns. This method prepares an elastic membrane from an input pattern and induces model-dependent pattern normalization by placing the membrane on each potential field representing a standard pattern.We composed a recognition system from non-linear normalization, coarse classification, model-dependent normalization and fine classification, then show that the system with the model-dependent normalization is more effective than that without it for both the ETL off-line handwritten character patterns database and the HANDS on-line patterns database.