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Document examiners use a variety of features to analyze a given handwritten document for writer verification. The challenge in the automatic classification of a pair of documents to belong to the same or different writer, are both the task of proper selection and extraction of features from the handwritten document and the use of a proper model that is capable of utilizing the true discriminatory power of these features for classification. This paper describes the use of content specific skeleton based features for characters and pairs of characters(bigrams) and ascertains their discriminatory power.
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