A Blind Indic Script Recognizer for Multi-script Documents

We report a hierarchical blind script identifier for 11 dif- ferent Indian scripts. An initial grouping of the 11 scripts is accomplished at the first level of this hierarchy. At the subsequent level, we recognize the script in each group. The various nodes of this tree use different feature-classifier combinations. A database of 20,000 words of different font styles and sizes is collected and used for each script. Ef- fectiveness of Gabor and Discrete Cosine Transform fea- tures has been independently evaluated using nearest neigh- bor, linear discriminant and support vector machine clas- sifiers. The minimum and maximum accuracies obtained, using this hierarchical mechanism, are 92.2% and 97.6%, respectively.