A segmentation-free approach to OCR is presented as part of a knowledge based word interpretation model. This method is based on the recognition of subgraphs homeomorphic to previously defined prototypes of characters. Gaps are identified as potential part of characters by implementing a variant of the notion of relative neighborhood used in computational perception. In the system, each subgraph of features that matches a previously defined character prototype is recognized anywhere in the word even if it corresponds to a broken character or to a character touching another one. Each subgraph that is recognized is introduced as a node in a direct net that compiles different alternatives of interpretation of the features in the feature graph. A final search for the optimal path under certain criteria gives the best interpretation of the word features. >
['Jairo Rocha', 'Theo Pavlidis']
A solution to the problem of touching and broken characters