Apply Multi-Layer Perceptrons Neural Network for Off-line signature verification and recognition

نویسندگان

  • Suhail Odeh
  • Manal Khalil
چکیده

This paper discusses the applying of Multi-layer perceptrons for signature verification and recognition using a new approach enables the user to recognize whether a signature is original or a fraud. The approach starts by scanning images into the computer, then modifying their quality through image enhancement and noise reduction, followed by feature extraction and neural network training, and finally verifies the authenticity of the signature. The paper discusses the different stages of the process including: image pre-processing, feature extraction and pattern recognition through neural networks.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Support vector machines versus multi-layer perceptrons for efficient off-line signature recognition

– The problem of automatic signature recognition has received little attention in comparison with the problem of signature verification despite its potential applications for accessing security-sensitive facilities and for processing certain legal and historical documents. This paper presents an efficient off-line human signature recognition system based on Support Vector Machines (SVM) and com...

متن کامل

Offline Signature Verification Using Surf Feature Extraction and Neural Networks Approach

In this paper we will evaluate the use of SURF features in handwritten signature verification. For each known writer we will take a sample of three genuine signatures and extract their SURF descriptors. In this paper, off-line signature recognition & verification using neural network is proposed, where the signature is captured and presented to the user in an image format. Signatures are verifi...

متن کامل

Off-line Handwritten Signature Recognition Using Wavelet Neural Network

ـــ ـ Automatic signature verification is a wellestablished and an active area for research with numerous applications such as bank check verification, ATM access, etc. Most off-Line signature verification systems depend on pixels intensity in feature extraction process which is sensitive to noise and any scale or rotation process on signature image. This paper proposes an off-line handwritten ...

متن کامل

Neural Network Based Offline Signature Recognition and Verification System

Handwritten signatures are the most natural way of authenticating a person’s identity. An offline signature verification system generally consists of four components: data acquisition, preprocessing, feature extraction, recognition and verification. This paper presents a method for verifying handwritten signature by using NN architecture. In proposed methods the multi-layer perceptron (MLP), mo...

متن کامل

Modeling of measurement error in refractive index determination of fuel cell using neural network and genetic algorithm

Abstract: In this paper, a method for determination of refractive index in membrane of fuel cell on basis of three-longitudinal-mode laser heterodyne interferometer is presented. The optical path difference between the target and reference paths is fixed and phase shift is then calculated in terms of refractive index shift. The measurement accuracy of this system is limited by nonlinearity erro...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011