![]() Thus the proposed scheme is efficient and can be used for many practical applications which require processing large volumes of data. All features are extracted globally from a given text block which does not require any complex and reliable segmentation of the document image into lines and characters. At the next stage, a sub-classification is performed based on script-specific features. In the first stage, the classifier groups the scripts into five major classes using global features. Such features are extracted from the responses of a multi-channel log-Gabor filter bank, designed at an optimal scale and multiple orientations. This scheme employs hierarchical classification which uses features consistent with human perception. ![]() ![]() ![]() In this paper, we present a scheme to identify different Indian scripts from a document image. Automatic identification of a script in a given document image facilitates many important applications such as automatic archiving of multilingual documents, searching online archives of document images and for the selection of script specific OCR in a multilingual environment.
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