Human Face Recognition using FSVD and RBF Neural Network

Kalpana Jondhale

ISBN 10: 620497873X / ISBN 13: 9786204978734

Published by LAP LAMBERT Academic Publishing, 2022

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - A Biometric system is a pattern recognition system. It operates by acquiring Biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against the template set in the database. A number of Biometric characteristics exist and are in use in various applications. Each Biometric has its strengths and weaknesses, and the choice depends on the application. The match between a specific Biometric with an application is determined depending upon the operational mode of the application and the properties of the Biometric characteristic. Research in automated face recognition has been conducted since the 1960s. The reliability of face recognition schemes still poses a great challenge to the scientific community. Face recognition has several advantages over other Biometric techniques. Face recognition is natural, non-intrusive and easy to use since it is based on images recorded by a distant camera and can be very effective even if the user is not aware of the existence of the face recognition system. The increased interest in automated face recognition systems have gained largely due to increasing public concerns for security.

Seller Inventory # 9786204978734

Bibliographic Details

• Title: Human Face Recognition using FSVD and RBF Neural Network
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2022
• Language: English
• ISBN 10: 620497873X
• ISBN 13: 9786204978734
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 9D millimeters 220 millimeters width by 150 millimeters height by 9 millimeters depth
• Weight: 227 grams

About this title

Synopsis

A Biometric system is a pattern recognition system. It operates by acquiring Biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against the template set in the database. A number of Biometric characteristics exist and are in use in various applications. Each Biometric has its strengths and weaknesses, and the choice depends on the application. The match between a specific Biometric with an application is determined depending upon the operational mode of the application and the properties of the Biometric characteristic. Research in automated face recognition has been conducted since the 1960s. The reliability of face recognition schemes still poses a great challenge to the scientific community. Face recognition has several advantages over other Biometric techniques. Face recognition is natural, non-intrusive and easy to use since it is based on images recorded by a distant camera and can be very effective even if the user is not aware of the existence of the face recognition system. The increased interest in automated face recognition systems have gained largely due to increasing public concerns for security.