The document discusses the importance of handwritten signature verification for computer security in financial transactions, highlighting its advantages as a cost-effective, reliable, and unobtrusive method. It outlines the challenges of online signature identification, including the need to differentiate between consistent and varying aspects of signatures, and presents a proposed workflow involving signature acquisition, pre-processing, feature extraction, and verification. Additionally, it mentions relevant applications in banking and identification, alongside the necessary hardware and software requirements for implementation.

1. Signature Verification
Using CNN
Submitted By:
Rachana Kulkarni (3747)
Sayali Kawale(3753)
Rifa Shazmeen(3755)

2. Introduction
 Computers are largely used in almost each and every field including financial
transactions, thus providing additional security measures for computer system is
necessary.
 The security measures to be used must be cheap, reliable and un-intrusive to the
authorized person. The technique which meets these requirements is handwritten
signature verification.

3. Why Handwritten Signature only ?
 Everyday transaction
 Individuals less likely to object
 Individual’s signature is unique
 Less controversial

4. Importance of Signature
 Transaction
 Individuals less likely to object
 Biometric

5. Types of Signature Identification
 Offline Signature Verification
 Deals with shape only
 Online Signature Verification
 Deals with dynamic features like speed, pen pressure, directions, stroke length, and
when the pen is lifted from the paper

6. Challenging tasks
 The main challenge with online Signature Identification technology is
differentiating between the consistent parts of the signature and the behavioural
parts of the signature that vary with each signing.
 A person’s signature is never entirely the same. Allowing for these variations while
providing protection against forgers is a challenging task.
 Differentiating between the parts of the signature that vary with each signing.
 The signature can vary substantially over an individual’s lifetime.

7. Proposed Work
 Signature Acquisition
 Signature Pre-processing
 Feature Extraction
 Signature Verification

8. Signature Acquisition
 Signature is acquired from the user

9. Signature Pre-processing
 Function of the pre-processor
• Image resizing
• Image binarizing
• Image thinning
• Image normalizing

10. Feature Extraction

11. Signature Identification

12. Applications
 Banking
 Passport office
 And any other places which require identification !

13. Advantages
 Low error rate
 Forgery is detected even when the forger has managed to get a copy of the
authentic signature
 Fast and simple training
 Cheap hardware
 Little storage requirements

14. Activity Diagram

15. Requirements & Technologies
 The hardware component we are using here is a scanning device(WEBCAM), high
RAM for better results and good processor.
 Operating System : Windows XP or Higher
 NetBeans IDE 7.0
 SDK – J2SE
 Intel core 2 duo processor
 2.1 GHZ, 1 GB RAM