access icon free Cosine similarity for analysis and verification of static signatures

The stability of handwritten signatures is a crucial characteristic for both investigating the nature of the signature apposition process and improving systems for automatic signature verification. In this study, a new technique for the analysis of stability in static signature images is discussed. The technique adopts a feature-based strategy to derive regional information from a static signature image and uses cosine similarity to estimate the degree of regional stability among genuine signatures, according to a multiple matching strategy. The experimental test carried out using signatures in the Grupo de Procesado Digital de Senales (GPDS) database has demonstrated the validity of this novel approach in obtaining stability information and deriving significant signer-independent and signer-dependent properties of the signing process, useful for verification aims.

Inspec keywords: handwriting recognition; statistical analysis; feature extraction; image matching

Other keywords: automatic static signature verification system improvement; feature-based strategy; matching strategy; static signature image stability analysis; cosine similarity; signing process signer-independent properties; handwritten signature apposition process; regional stability degree estimation; signing process signer-dependent properties; GPDS database

Subjects: Other topics in statistics; Other topics in statistics; Image recognition; Computer vision and image processing techniques

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