Signature Recognition Using Clustering Techniques | Vector Quantization based Approach for Static Signature Recognition

Vinayak Bharadi (u. a.)

ISBN 10: 384844755X / ISBN 13: 9783848447558

Published by LAP Lambert Academic Publishing, 2012

About this Item

Signature Recognition Using Clustering Techniques | Vector Quantization based Approach for Static Signature Recognition | Vinayak Bharadi (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783848447558 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 106571039

Bibliographic Details

• Title: Signature Recognition Using Clustering Techniques | Vector Quantization based Approach for Static Signature Recognition
• Publisher: LAP Lambert Academic Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 384844755X
• ISBN 13: 9783848447558
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 150W x 10H x 219D millimeters 150 millimeters width by 10 millimeters height by 219 millimeters depth
• Weight: 317 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

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.

About the Author

Dr. V. A. Bharadi has received B.E. Electronics Engg.in 2002 & M. E. Electronics & Telecomm in 2007 from Mumbai University. He has completed Ph.D. in Engineering (Biometrics Authentication Systems) from NMIMS University in 2011. He has worked Over 9 years as a faculty of Electronics & IT Engg. He has published 50+ National & International papers.