Recognition of Signature Using Neural Network and Euclidean Distance for Bank Cheque Automation

Title

Recognition of Signature Using Neural Network and Euclidean Distance for Bank Cheque Automation

Creator

Raghavendra S.P.; Danti A.

Description

Handwritten signature recognition plays significant role in automatic document verification system in particularly bank cheque authorization. The proposed method focuses on A novel technique for offline signature recognition approach for bank cheque based on zonal features and regional features. These combined features are used to find genuinety of signature using Euclidean distance as a metric. Extensive experiments are carried out to exhibit the success of the recommended approach. 2019, Springer Nature Singapore Pte Ltd.

Source

Communications in Computer and Information Science, Vol-1037, pp. 228-243.

Date

2019-01-01

Publisher

Springer Verlag

Subject

Euclidean distance measure; Neural network; Signature recognition; Zonal features

Coverage

Raghavendra S.P., NES Research Foundation, Department of MCA, JNNCE, Shimoga, Karnataka, India; Danti A., Department of Computer Science and Engineering, Christ (Deemed to be university), Bangalore, Karnataka, India

Rights

Restricted Access

Relation

ISSN: 18650929; ISBN: 978-981139186-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-13-9187-3_21

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070198600&doi=10.1007%2f978-981-13-9187-3_21&partnerID=40&md5=8a8d177dbc8464892090e2c61b978fbc