Abstract: A computer-implemented process identifies an unknown language used to create a document. A set of training documents is defined in a variety of known languages and formed from a variety of text styles. Black and white electronic pixel images are formed of text material forming the training documents and the document in the unknown language. A plurality of line strokes are defined from the black pixels and point features are extracted from the strokes that are effective to characterize each of the languages. Point features from the unknown language are compared with point features from the known languages to identify one of the known languages that best represents the unknown language.

Abstract: A computer-implemented method identifies a script used to create a document. A set of training documents for each script to be identified is scanned into the computer to store a series of exemplary images representing each script. Pixels forming the exemplary images are electronically processed to define a set of textual symbols corresponding to the exemplary images. Each textual symbol is assigned to a cluster of textual symbols that most closely represents the textual symbol. The cluster of textual symbols is processed to form a representative electronic template for each cluster. A document having a script to be identified is scanned into the computer to form one or more document images representing the script to be identified. Pixels forming the document images are electronically processed to define a set of document textual symbols corresponding to the document images. The set of document textual symbols is compared to the electronic templates to identify the script.