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In searching a repository of business documents, a task of interest is that of using a query signature image to retrieve from a database, other signatures matching the query. The signature retrieval task involves a two-step process of extracting all the signatures from the documents and then performing a match on these signatures. This paper presents a novel signature retrieval strategy, which includes a technique for noise and printed text removal from signature images, previously extracted from business documents. Signature matching is based on a normalized correlation similarity measure using global shape-based binary feature vectors. In a retrieval task involving a database of 447 signatures, on an average 4.43 out of the top 5 choices were signatures belonging to the writer of the queried signature. On considering the Top 10 ranks, a F-measure value of 76.3 was obtained and the precision and recall values at this F-measure were 74.5% and 78.28% respectively
Srihari et al. (Thu,) studied this question.