Biometric authentication techniques are in high demand for entrance
monitoring and security systems. The techniques must be cheap,
reliable and, simple. Handwritten signature verification satisfies
these requirements. Signature Recognition is a very well known area
in Biometrics. Signature of a person is one of the important
biometric attribute, has been used for centuries as an
authentication measure. In current era signatures are important in
business, banking, legal application areas. With the tremendous
developments in computer technology and advancements in programming
platforms the field of biometrics has seen increments with leaps
and bounds. In this book we have discussed an automatic off-line
signature verification and forgery detection system based on
clustering technique. This system uses the Vector Quantization,
Walsh Coefficients, Geometric centers, Grid and Texture features as
well as local and Global features of a static handwritten
signature.
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