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Signature is one of the most widely used biometric traits for authentication of person as well as document as proofs. The biometrics is most commonly defined as measurable psychological or behavioral characteristic of the person that can be used in personal identification and verification. In this book, we have addressed the problem of Kannada signature identification and verification system. As part of the system is concerned, signature written with a skew is a hurdle to the system. An efficient skew estimation technique is introduced for the same. Feature representation plays a vital role in any recognition system. We have explored the concept of Kernel methods and ICA for efficient feature representation. HOG features combined with kernel methods is also used for verification system. Extensive experiments are carried out in order to show the effectiveness of the proposed approaches.