Online Store - 8925533488 /89

Chennai - 8925533480 /81

Hyderabad - 8925533482 /83

Vijayawada -8925533484 /85

Covai - 8925533486 /87

Online Signature Verification using Convolutional Neural Network (CNN) and OpenCV

( 0 Rating )
Shape Image One
0 student


This paper studies online signature verification on touch interface-based mobile devices. A simple and effective method for signature verification is developed. An online signature is represented with a discriminative feature vector derived from attributes of several histograms that can be computed in linear time. The resulting signature template is compact and requires constant space. The algorithm was first tested on the well-known MCYT-100 and SUSIG data sets. The results show that the performance of the proposed technique is comparable and often superior to state-of-the-art algorithms despite its simplicity and efficiency. In order to test the proposed method on signatures on camera capture devices, a data set was collected from an uncontrolled environment and over multiple sessions. Experimental results on this data set confirm the effectiveness of the proposed algorithm in mobile settings. The results demonstrate the problem of within-user variation of signatures across multiple sessions and the effectiveness of cross session training strategies to alleviate these problems.


Existing Method:

Features Extraction process

  • Static approaches-The static one involves geometric measures of the signature,
  • Pseudo-dynamic approaches-Automatic static handwritten signature verification based on the use of gray level values from signature stroke pixels.


Draw Backs:

  • Accuracy is less.
  • Illumination occurrences is less
  • Error Rate is more


 Proposed Method:

Behavioral Biometric Application

  • Online signature (Data Set Images)
  • Template aging,

Performance evaluation,


Block Diagram:

Signature Verification Using CNN

Software Requirement:

  • Python Idle
  • Numpy
  • Opencv
Curriculum is empty

pantech team

Agile Project Expert

Course Rating

0.00 average based on 0 ratings

Course Preview
  • Price
  • Instructor pantech team
  • Duration 15 Hrs
  • Enrolled 0 student
  • Access 3 Months

More Things You Might Like This


Student Performance Prediction using Machine Learning

Abstract: Although the educational level of the Portuguese population has improved in the last decades, the statistics keep Portugal at Europe’s tail end due to its high student failure rates. In particular, lack of success in the core classes of Mathematics and the Portuguese language is extremely serious. On the other hand, the fields of


Student feedback analysis

Abstract: Advances in natural language processing (NLP) and educational technology, as well as the availability of unprecedented amounts of educationally-relevant text and speech data, have led to an increasing interest in using NLP to address the needs of teachers and students. Educational applications differ in many ways, however, from the types of applications for which


Machine Learning based Regression Model for Prediction of Soil Surface Humidity over Moderately Vegetated Fields

Abstract: Agriculture is one of the major revenue producing sectors of India and a source of survival. Numerous seasonal, economic and biological patterns influence the crop production but unpredictable changes in these patterns lead to a great loss to farmers. These risks can be reduced when suitable approaches are employed on data related to soil

Open Whatsapp Chat
Need Any Help?
Welcome to Pantech eLearning!..

How can i help you?