This document summarizes several computer vision and soft computing techniques that have been used for offline signature verification and forgery detection in previous research studies. It discusses techniques like fuzzy logic, artificial neural networks, feature extraction methods, and related systems developed by other researchers that have used approaches like neural networks trained on local and global features to classify signatures. The document also provides a brief introduction to concepts like computer vision technology, the need for automated signature verification systems, and defines terms like soft computing and discusses some common soft computing techniques.
IRJET- Handwritten Signature Verification using Local Binary Pattern Features...IRJET Journal
This document summarizes an research paper on offline handwritten signature verification using local binary pattern features and K-nearest neighbors classification. It describes preprocessing signatures using Otsu thresholding, extracting local binary pattern features, and classifying signatures with KNN. 40 signature recognition approaches were reviewed before designing this system. The system achieved an accuracy of 85% on a dataset of bank cheque signatures during testing.
This document presents a statistical-ANN hybrid technique for offline signature recognition. It extracts features from signatures using statistical approaches like invariant moment methods, and then classifies signatures using an artificial neural network (ANN). The system takes in signature images, preprocesses them, extracts features, and trains an ANN classifier. It can recognize and verify signatures on a test database with reasonable accuracy. The hybrid statistical-ANN approach aims to minimize intra-personal variations between genuine signatures while maximizing inter-personal variations to distinguish forgeries.
This document describes the design and implementation of a fingerprint-based identity authentication system. The system uses an improved algorithm to extract minutiae features from fingerprints faster and more accurately than previous methods. It then employs an alignment-based matching algorithm to find correspondences between input and stored fingerprint templates without exhaustive search. Experimental results on standard fingerprint databases show the system can achieve good performance and satisfy response time requirements for authentication, taking about 1.4 seconds on average. The system provides a means of positive identity verification through fingerprint biometrics with a very high level of accuracy.
Design of digital signature verification algorithm using relative slope methodeSAT Publishing House
This document summarizes a research paper that proposes a new algorithm for signature verification using a digital pen. The algorithm analyzes the relative slopes of a signature's segments to determine if a signature matches one stored in a database. It works by segmenting the signature, calculating the slope of each segment relative to the previous one, and storing these slope values. During verification, it compares the stored and input slope values, alongside other dynamic features like writing speed and pressure, and determines a match percentage. The paper finds that this relative slope method improves the accuracy and parameters of previous signature verification systems.
11.graphical password based hybrid authentication system for smart hand held ...Alexander Decker
Ray's Scheme is a proposed hybrid graphical password authentication system for smart handheld devices. The system combines recognition and recall-based techniques and has two phases: registration and authentication. During registration, the user selects a username, textual password, and graphical password by choosing objects and corresponding digits. During authentication, the user enters their username, password, and recalls the graphical password by selecting the objects and entering the digits. The system aims to provide more security while being user-friendly for smart devices.
A Survey Based on Fingerprint Matching SystemIJTET Journal
Abstract — Fingerprint is one of the biometric features mostly used for identification and verification. Latent fingerprints are conventionally recovered coming in to existence of crime scenes and are analyzed with active databases of well-known fingerprints for finding criminals. A bulk of matching algorithms with distant uniqueness has been developed in modern years and the algorithms are depending up on minutiae features. The detection of accepted systems tries to find which fingerprint in a database matches the fingerprint needs the matching of its minutiae against the input fingerprint. Since the detection complexity are more minutiae of other fingerprints. Therefore, fingerprint matching system is a higher than verification and detection systems. This paper discussed about the various novel techniques like Minutia Cylinder Code (MCC) algorithm, Minutia score matching and Graphic Processing Unit (GPU). The feature extraction anywhere in the extracted features is sovereign of shift and rotation of the fingerprint. Meanwhile, the matching operation is performed much more easily and higher accuracy.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Biometric Template Protection With Robust Semi – Blind Watermarking Using Ima...CSCJournals
This paper addresses a biometric watermarking technology sturdy towards image manipulations, like JPEG compression, image filtering, and additive noise. Application scenarios include information transmission between client and server, maintaining e-database and management of signatures through insecure distribution channels. Steps involved in this work are, a) generation of binary signature code for biometric, b) embedding of the binary signature to the host image using intrinsic local property, that ensures signature protection, c) host image is then made exposed to various attacks and d) signature is extracted and matched based on an empirical threshold to verify the robustness of proposed embedding method. Embedding relies on binary signature manipulating the lower order AC coefficients of Discrete Cosine Transformed sub-blocks of host image. In the prediction phase, DC values of the nearest neighbor DCT blocks is utilized to predict the AC coefficients of centre block. Surrounding DC values of a DCT blocks are adaptively weighed for AC coefficients prediction. Linear programming is used to calculate the weights with respect to the image content. Multiple times embedding of watermark ensures robustness against common signal processing operations (filtering, enhancement, rescaling etc.) and various attacks. The proposed algorithm is tested for 50 different types of host images and public data collection, DB3, FVC2002. FAR and FRR are compared with other methods to show the improvement.
IRJET- Handwritten Signature Verification using Local Binary Pattern Features...IRJET Journal
This document summarizes an research paper on offline handwritten signature verification using local binary pattern features and K-nearest neighbors classification. It describes preprocessing signatures using Otsu thresholding, extracting local binary pattern features, and classifying signatures with KNN. 40 signature recognition approaches were reviewed before designing this system. The system achieved an accuracy of 85% on a dataset of bank cheque signatures during testing.
This document presents a statistical-ANN hybrid technique for offline signature recognition. It extracts features from signatures using statistical approaches like invariant moment methods, and then classifies signatures using an artificial neural network (ANN). The system takes in signature images, preprocesses them, extracts features, and trains an ANN classifier. It can recognize and verify signatures on a test database with reasonable accuracy. The hybrid statistical-ANN approach aims to minimize intra-personal variations between genuine signatures while maximizing inter-personal variations to distinguish forgeries.
This document describes the design and implementation of a fingerprint-based identity authentication system. The system uses an improved algorithm to extract minutiae features from fingerprints faster and more accurately than previous methods. It then employs an alignment-based matching algorithm to find correspondences between input and stored fingerprint templates without exhaustive search. Experimental results on standard fingerprint databases show the system can achieve good performance and satisfy response time requirements for authentication, taking about 1.4 seconds on average. The system provides a means of positive identity verification through fingerprint biometrics with a very high level of accuracy.
Design of digital signature verification algorithm using relative slope methodeSAT Publishing House
This document summarizes a research paper that proposes a new algorithm for signature verification using a digital pen. The algorithm analyzes the relative slopes of a signature's segments to determine if a signature matches one stored in a database. It works by segmenting the signature, calculating the slope of each segment relative to the previous one, and storing these slope values. During verification, it compares the stored and input slope values, alongside other dynamic features like writing speed and pressure, and determines a match percentage. The paper finds that this relative slope method improves the accuracy and parameters of previous signature verification systems.
11.graphical password based hybrid authentication system for smart hand held ...Alexander Decker
Ray's Scheme is a proposed hybrid graphical password authentication system for smart handheld devices. The system combines recognition and recall-based techniques and has two phases: registration and authentication. During registration, the user selects a username, textual password, and graphical password by choosing objects and corresponding digits. During authentication, the user enters their username, password, and recalls the graphical password by selecting the objects and entering the digits. The system aims to provide more security while being user-friendly for smart devices.
A Survey Based on Fingerprint Matching SystemIJTET Journal
Abstract — Fingerprint is one of the biometric features mostly used for identification and verification. Latent fingerprints are conventionally recovered coming in to existence of crime scenes and are analyzed with active databases of well-known fingerprints for finding criminals. A bulk of matching algorithms with distant uniqueness has been developed in modern years and the algorithms are depending up on minutiae features. The detection of accepted systems tries to find which fingerprint in a database matches the fingerprint needs the matching of its minutiae against the input fingerprint. Since the detection complexity are more minutiae of other fingerprints. Therefore, fingerprint matching system is a higher than verification and detection systems. This paper discussed about the various novel techniques like Minutia Cylinder Code (MCC) algorithm, Minutia score matching and Graphic Processing Unit (GPU). The feature extraction anywhere in the extracted features is sovereign of shift and rotation of the fingerprint. Meanwhile, the matching operation is performed much more easily and higher accuracy.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Biometric Template Protection With Robust Semi – Blind Watermarking Using Ima...CSCJournals
This paper addresses a biometric watermarking technology sturdy towards image manipulations, like JPEG compression, image filtering, and additive noise. Application scenarios include information transmission between client and server, maintaining e-database and management of signatures through insecure distribution channels. Steps involved in this work are, a) generation of binary signature code for biometric, b) embedding of the binary signature to the host image using intrinsic local property, that ensures signature protection, c) host image is then made exposed to various attacks and d) signature is extracted and matched based on an empirical threshold to verify the robustness of proposed embedding method. Embedding relies on binary signature manipulating the lower order AC coefficients of Discrete Cosine Transformed sub-blocks of host image. In the prediction phase, DC values of the nearest neighbor DCT blocks is utilized to predict the AC coefficients of centre block. Surrounding DC values of a DCT blocks are adaptively weighed for AC coefficients prediction. Linear programming is used to calculate the weights with respect to the image content. Multiple times embedding of watermark ensures robustness against common signal processing operations (filtering, enhancement, rescaling etc.) and various attacks. The proposed algorithm is tested for 50 different types of host images and public data collection, DB3, FVC2002. FAR and FRR are compared with other methods to show the improvement.
The document is a seminar report submitted by Nikita Sanjay Rajbhoj to Prof. Ashwini Jadhav at G.S. Moze College of Engineering. It discusses big data, including its definition, characteristics, architecture, technologies, and applications. The report includes an abstract, introduction, and sections on definition, characteristics, architecture, technologies, and applications of big data. It also includes references, acknowledgements, and certificates.
This document provides a comprehensive review of vision-based hand gesture recognition technology. It discusses different approaches to vision-based hand gesture recognition including appearance-based and model-based approaches. Appearance-based approaches model gestures based on image properties and views, while model-based approaches use 3D models to represent hand posture. The document also reviews several papers on specific hand gesture recognition systems and compares their segmentation methods, feature extraction techniques, representations, and classification algorithms. Finally, it discusses applications of vision-based hand gesture recognition including as an alternative to touchscreens and in areas like sign language recognition, gaming, and robot control.
The document discusses gesture-based computing as an alternative to mouse input for human-computer interaction. It proposes a novel approach for implementing a real-time gesture recognition system capable of understanding commands based on analyzing the principal contour and fingertips of hand gestures. Vision-based gesture recognition techniques are discussed that do not require additional devices for users to interact with computers through natural hand motions.
novel method of identifying fingerprint using minutiae matching in biometric ...INFOGAIN PUBLICATION
Fingerprint is one of the best apparatus to identify human because of its uniqueness, details information, hard to change and long-term indicators of human identity where there are several biometric feature that can be recycled to endorse the individuality. Identification of fingerprint is very important in forensic science, trace any part of human, collection of crime part and proof from a crime. This paper presents a new method of identifying fingerprint in biometrics security system. Fingerprint is one of the best example in biometric security because it can identify personal information and it is much secure than any other biometric identification system. The experimental result exhibits the performance of the proposed method.
Handwritten Signature Verification using Artificial Neural NetworkEditor IJMTER
This paper reviews various Signature Verification approaches; various feature sets,
various online databases and types of features. Processing on an online database, post extracting a
combination of global and local features onto a signature as an image, using MultiLayer Perceptron Feed
Forward Network alongwith Back Propogation Algorithm for training is proposed to classify a genuine
and forged (random, simple and skilled) offline signatures.
India is one of the countries which has the electronic voting machine for parliamentary and assembly polls. But in every poll election commission is facing so much of troubles and various types of issues through the election. The most familiar issue which is faced by the election commission is, no proper acknowledgement regarding the confirmation of casting the votes, duplication or illegal casting of votes. In this project all these issues has been handled and overcome with the perfect solution. The main advantage of this project is handling of data by using biometric system such as finger print and face recognition (is done by masking technique). This is used to ensure the security to avoid fake and repeating voting. It also enhances the accuracy and speed of the process. The system performs with perfect recognition on a face and thumb impression of all the eligible voters in a constituency, which is done as pre-polled procedure. During election, thumb impression and face templates of voters is given as an input to the system. This is then compared with the already stored database and available records. If the particular pattern matches with the record then the voters are allowed to vote but incase if it doesn’t match or in case of repetition, voters vote are denied or gets rejected. The result is instant and counting is done.
Overlapped Fingerprint Separation for Fingerprint AuthenticationIJERA Editor
Overlapped fingerprints captured at the crime scene plays significant role as an evidence to capture the criminals. As latent fingerprints are the accidently left skin impressions, so these are found to be with broken ridge composition, overlapped patterns and spoiled minutiae information. The Graphical User Interface (GUI) system is developed by using MATLAB R2015a software. This project also includes the development of standalone program for this system. The main purpose of GUI development is to get the value of real end points and real-branch points of a overlapped fingerprint image. The value of this point is used in fingerprint image matching process to identify the owner of an overlapped fingerprint image. The image enhancement consists of several process such as histogram equalization process, enhancement by Fast Fourier Transform (FFT) factor, and image binarization while minutiae extraction consist of ridge thinning process, region of interest (ROI) extraction, and minutiae extraction process. All processes should be done one by one.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document summarizes a research paper that proposes using fragile watermarking techniques to hide additional information in fingerprint images. This helps address vulnerabilities in biometric identification systems by allowing authentication of fingerprint image integrity. The proposed framework embeds watermarks in fingerprint templates during enrollment. During verification, watermarks are extracted to authenticate templates before matching. Experimental results show watermarks can be embedded with little quality impact and no effect on matching performance. The technique helps detect if templates are tampered with by unauthorized parties.
A Review on Robust identity verification using signature of a personEditor IJMTER
Signature is behavioural type biometrics characteristics of human. Signature has been a
distinguishing feature for person identification. In these days increasing number of transactions,
especially related to financial and business are being authorized via signatures. Two types of
verification methods are: Offline signature verification and online signature verification. In this paper
we review various components of offline signature reorganization and verification system, feature
extraction techniques and available techniques.
Effectiveness of various user authentication techniquesIAEME Publication
This document discusses and compares various user authentication techniques. It analyzes one-time password authentication using smart phones (oPass), 3D password authentication using a virtual environment, and smart card-based authentication. oPass requires the user to remember only a long-term password for their phone, while the website generates one-time passwords via SMS. 3D passwords combine multiple authentication methods by having users navigate and interact with virtual objects. Smart card authentication does not store passwords in verification tables and allows password changes for mutual authentication. The document examines the advantages and disadvantages of these approaches.
HMM-Based Face Recognition System with SVD Parameterijtsrd
Today an increasing digital world, personal reliable authentication has become an important human Computer interface activity. It is very important to establish a persons identity. In today existing security mainly depends on passwords, swipe cards or token based approach and attitude to control access to physical and virtual spaces passport. Universal, such as methods, although very secure. Such as tokens, badges and access cards can be shared or stolen. Passwords and PIN numbers can be also stolen electronically. In addition, they cannot distinguish between authentic have access to or knowledge of the user and tokens. To make a system more secure and simple with the use of biometric authentication system such as face and hand gesture recognition for personal authentication. So in this paper, A Hidden Markov Model (HMM) based face recognition system using Singular Value Decomposition (SVD) is proposed. Neha Rana | Bhavna Pancholi"HMM-Based Face Recognition System with SVD Parameter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd12938.pdf http://www.ijtsrd.com/engineering/electrical-engineering/12938/hmm-based-face-recognition-system-with-svd-parameter/neha-rana
This document describes a proposed sign language interpreter system that uses machine learning and computer vision techniques. It aims to enable deaf and mute users to communicate through computers and the internet by recognizing static hand gestures from camera input and translating them to text. The proposed system extracts features from captured images of signs and uses a support vector machine model to classify the gestures by comparing to a dataset of labeled images. If implemented, this system could help overcome communication barriers for deaf users in an increasingly digital world.
A Comparison Based Study on Biometrics for Human RecognitionIOSR Journals
Abstract: A biometric system provides automatic recognition of an individual based on a unique feature or
characteristic possessed by the individual. These biometric characteristic may physiological or behavioral.
Unlike other identification methods such as id proof, tokens and password, the distinct aspect of biometric
recognition comes into light from randomly distributed features in human being. In this paper, I describe the
novel comparison based upon various aspects to make easy selection for biometric device deployment in specific
environment. This paper proposes a comparison among all kind of biometric system available in the society.
The existing computer security systems used at various places like banking, passport, credit cards, smart cards,
PIN , access control and network security are using username and passwords for person identification.
Biometric systems also introduce an aspect of user convenience; it means one can be authorized by representing
himself or herself. In this paper, the main focus is on working principal of biometric technique, the various
biometrics systems and their comparisons.
Keywords: Biometrics, authentication, identification, recognition
FEATURE EXTRACTION METHODS FOR IRIS RECOGNITION SYSTEM: A SURVEYijcsit
This document summarizes several feature extraction methods for iris recognition systems. It discusses supervised, unsupervised, and semi-supervised learning approaches for iris recognition. It also reviews related literature on iris recognition techniques, including using wavelet transforms, SVM classifiers, and other feature extraction methods. Tables in the document compare different biometric traits and traditional biometric systems, as well as summarize reviewed articles on iris recognition with their main contributions. The methodology section describes the typical four steps of an iris recognition system: image acquisition, preprocessing, feature extraction, and matching/recognition. It also discusses various iris recognition methods and their performance measures.
Advanced Authentication Scheme using Multimodal Biometric SchemeEditor IJCATR
This document presents a study on using multimodal biometrics with palm and fingerprint recognition to improve identification accuracy. The authors first discuss existing unimodal biometrics and limitations. They then describe the typical steps in a multimodal system: image capture, preprocessing, feature extraction, fusion, and matching. For this study, minutiae extraction is used to extract fingerprint features while local binary patterns extract palm features. Wavelet fusion is applied to the extracted features before support vector machine matching. The authors aim to demonstrate that combining palm and fingerprint biometrics can achieve better performance than single biometrics alone.
This document proposes a system for strengthening security for online banking transactions. It involves multi-level authentication including face recognition, graphical OTP authentication using a 4x4 grid of random numbers, and security questions. Users first register security images, a security pattern by selecting indexes on a 4x4 grid, answers to security questions, and their face is recorded. For login, the security images and username/password are verified. Transactions require face recognition if a webcam is available, otherwise graphical OTP authentication is used where the user selects numbers from the indexes of their security pattern on a randomly generated 4x4 grid. Additionally, two random security questions are asked before completing a transaction. The system aims to provide secure electronic transactions through this multi-factor
Pre-Processing Image Algorithm for Fingerprint Recognition and its Implementa...ijseajournal
This document discusses a pre-processing image algorithm for fingerprint recognition and its implementation on a DSP TMS320C6416. It first presents the pre-processing steps used to improve fingerprint image quality, such as grayscale transformation, normalization, segmentation, and Gabor filtering. It then discusses implementing the algorithm on the TMS320C6416 DSP hardware platform, which features a 600MHz processor, internal and external memory, and cache memories. The DSP platform allows for fast, powerful image processing needed for real-time fingerprint recognition applications.
This document proposes a grid-based feature extraction method for offline signature verification. It begins with an introduction and discusses existing techniques and their limitations. It then presents the proposed work, which involves signature acquisition, preprocessing, feature extraction by segmenting the signature image into a grid, and verification. The algorithms, mathematical model, advantages and applications are described. The document concludes that the proposed method requires only low-cost hardware and has a low error rate for signature verification.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
PREPROCESSING ALGORITHM FOR DIGITAL FINGERPRINT IMAGE RECOGNITION ijcsity
Biometrics is one of the most used technologies in the field of security due to its reliability and
performance. It is based on several physical human characteristics but the most used technology is the
fingerprint recognition, and since we must carry out an image processing to be able to exploit the data in
each fingerprint we propose in this article an image preprocessing procedure in order to improve its
quality before extracting the necessary information for the comparison phase.
A SURVEY ON DEEP LEARNING METHOD USED FOR CHARACTER RECOGNITIONIJCIRAS Journal
The field of Artificial Intelligence is very fashionable today, especially neural networks that work well in various areas such as speech recognition and natural language processing. This Research Article briefly describes how deep learning models work and what different techniques are used in text recognition. It also describes the great progress that has been made in the field of medicine, the analysis of forensic documents, the recognition of license plates, banking, health and the legal industry. The recognition of handwritten characters is one of the research areas in the field of artificial intelligence. The individual character recognition has a higher recognition accuracy than the complete word recognition. The new method for categorizing Freeman strings is presented using four connectivity events and eight connectivity events with a deep learning approach.
A Smart Receptionist Implementing Facial Recognition and Voice InteractionCSCJournals
The purpose of this research is to implement a smart receptionist system with facial recognition and voice interaction using deep learning. The facial recognition component is implemented using real time image processing techniques, and it can be used to learn new faces as well as detect and recognize existing faces. The first time a customer uses this system, it will take the person’s facial data to create a unique user facial model, and this model will be triggered if the person comes the second time. The recognition is done in real time and after which voice interaction will be applied. Voice interaction is used to provide a life-like human communication and improve user experience. Our proposed smart receptionist system could be integrated into the self check-in kiosks deployed in hospitals or smart buildings to streamline the user recognition process and provide customized user interactions. This system could also be used in smart home environment where smart cameras have been deployed and voice assistants are in place.
The document is a seminar report submitted by Nikita Sanjay Rajbhoj to Prof. Ashwini Jadhav at G.S. Moze College of Engineering. It discusses big data, including its definition, characteristics, architecture, technologies, and applications. The report includes an abstract, introduction, and sections on definition, characteristics, architecture, technologies, and applications of big data. It also includes references, acknowledgements, and certificates.
This document provides a comprehensive review of vision-based hand gesture recognition technology. It discusses different approaches to vision-based hand gesture recognition including appearance-based and model-based approaches. Appearance-based approaches model gestures based on image properties and views, while model-based approaches use 3D models to represent hand posture. The document also reviews several papers on specific hand gesture recognition systems and compares their segmentation methods, feature extraction techniques, representations, and classification algorithms. Finally, it discusses applications of vision-based hand gesture recognition including as an alternative to touchscreens and in areas like sign language recognition, gaming, and robot control.
The document discusses gesture-based computing as an alternative to mouse input for human-computer interaction. It proposes a novel approach for implementing a real-time gesture recognition system capable of understanding commands based on analyzing the principal contour and fingertips of hand gestures. Vision-based gesture recognition techniques are discussed that do not require additional devices for users to interact with computers through natural hand motions.
novel method of identifying fingerprint using minutiae matching in biometric ...INFOGAIN PUBLICATION
Fingerprint is one of the best apparatus to identify human because of its uniqueness, details information, hard to change and long-term indicators of human identity where there are several biometric feature that can be recycled to endorse the individuality. Identification of fingerprint is very important in forensic science, trace any part of human, collection of crime part and proof from a crime. This paper presents a new method of identifying fingerprint in biometrics security system. Fingerprint is one of the best example in biometric security because it can identify personal information and it is much secure than any other biometric identification system. The experimental result exhibits the performance of the proposed method.
Handwritten Signature Verification using Artificial Neural NetworkEditor IJMTER
This paper reviews various Signature Verification approaches; various feature sets,
various online databases and types of features. Processing on an online database, post extracting a
combination of global and local features onto a signature as an image, using MultiLayer Perceptron Feed
Forward Network alongwith Back Propogation Algorithm for training is proposed to classify a genuine
and forged (random, simple and skilled) offline signatures.
India is one of the countries which has the electronic voting machine for parliamentary and assembly polls. But in every poll election commission is facing so much of troubles and various types of issues through the election. The most familiar issue which is faced by the election commission is, no proper acknowledgement regarding the confirmation of casting the votes, duplication or illegal casting of votes. In this project all these issues has been handled and overcome with the perfect solution. The main advantage of this project is handling of data by using biometric system such as finger print and face recognition (is done by masking technique). This is used to ensure the security to avoid fake and repeating voting. It also enhances the accuracy and speed of the process. The system performs with perfect recognition on a face and thumb impression of all the eligible voters in a constituency, which is done as pre-polled procedure. During election, thumb impression and face templates of voters is given as an input to the system. This is then compared with the already stored database and available records. If the particular pattern matches with the record then the voters are allowed to vote but incase if it doesn’t match or in case of repetition, voters vote are denied or gets rejected. The result is instant and counting is done.
Overlapped Fingerprint Separation for Fingerprint AuthenticationIJERA Editor
Overlapped fingerprints captured at the crime scene plays significant role as an evidence to capture the criminals. As latent fingerprints are the accidently left skin impressions, so these are found to be with broken ridge composition, overlapped patterns and spoiled minutiae information. The Graphical User Interface (GUI) system is developed by using MATLAB R2015a software. This project also includes the development of standalone program for this system. The main purpose of GUI development is to get the value of real end points and real-branch points of a overlapped fingerprint image. The value of this point is used in fingerprint image matching process to identify the owner of an overlapped fingerprint image. The image enhancement consists of several process such as histogram equalization process, enhancement by Fast Fourier Transform (FFT) factor, and image binarization while minutiae extraction consist of ridge thinning process, region of interest (ROI) extraction, and minutiae extraction process. All processes should be done one by one.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document summarizes a research paper that proposes using fragile watermarking techniques to hide additional information in fingerprint images. This helps address vulnerabilities in biometric identification systems by allowing authentication of fingerprint image integrity. The proposed framework embeds watermarks in fingerprint templates during enrollment. During verification, watermarks are extracted to authenticate templates before matching. Experimental results show watermarks can be embedded with little quality impact and no effect on matching performance. The technique helps detect if templates are tampered with by unauthorized parties.
A Review on Robust identity verification using signature of a personEditor IJMTER
Signature is behavioural type biometrics characteristics of human. Signature has been a
distinguishing feature for person identification. In these days increasing number of transactions,
especially related to financial and business are being authorized via signatures. Two types of
verification methods are: Offline signature verification and online signature verification. In this paper
we review various components of offline signature reorganization and verification system, feature
extraction techniques and available techniques.
Effectiveness of various user authentication techniquesIAEME Publication
This document discusses and compares various user authentication techniques. It analyzes one-time password authentication using smart phones (oPass), 3D password authentication using a virtual environment, and smart card-based authentication. oPass requires the user to remember only a long-term password for their phone, while the website generates one-time passwords via SMS. 3D passwords combine multiple authentication methods by having users navigate and interact with virtual objects. Smart card authentication does not store passwords in verification tables and allows password changes for mutual authentication. The document examines the advantages and disadvantages of these approaches.
HMM-Based Face Recognition System with SVD Parameterijtsrd
Today an increasing digital world, personal reliable authentication has become an important human Computer interface activity. It is very important to establish a persons identity. In today existing security mainly depends on passwords, swipe cards or token based approach and attitude to control access to physical and virtual spaces passport. Universal, such as methods, although very secure. Such as tokens, badges and access cards can be shared or stolen. Passwords and PIN numbers can be also stolen electronically. In addition, they cannot distinguish between authentic have access to or knowledge of the user and tokens. To make a system more secure and simple with the use of biometric authentication system such as face and hand gesture recognition for personal authentication. So in this paper, A Hidden Markov Model (HMM) based face recognition system using Singular Value Decomposition (SVD) is proposed. Neha Rana | Bhavna Pancholi"HMM-Based Face Recognition System with SVD Parameter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd12938.pdf http://www.ijtsrd.com/engineering/electrical-engineering/12938/hmm-based-face-recognition-system-with-svd-parameter/neha-rana
This document describes a proposed sign language interpreter system that uses machine learning and computer vision techniques. It aims to enable deaf and mute users to communicate through computers and the internet by recognizing static hand gestures from camera input and translating them to text. The proposed system extracts features from captured images of signs and uses a support vector machine model to classify the gestures by comparing to a dataset of labeled images. If implemented, this system could help overcome communication barriers for deaf users in an increasingly digital world.
A Comparison Based Study on Biometrics for Human RecognitionIOSR Journals
Abstract: A biometric system provides automatic recognition of an individual based on a unique feature or
characteristic possessed by the individual. These biometric characteristic may physiological or behavioral.
Unlike other identification methods such as id proof, tokens and password, the distinct aspect of biometric
recognition comes into light from randomly distributed features in human being. In this paper, I describe the
novel comparison based upon various aspects to make easy selection for biometric device deployment in specific
environment. This paper proposes a comparison among all kind of biometric system available in the society.
The existing computer security systems used at various places like banking, passport, credit cards, smart cards,
PIN , access control and network security are using username and passwords for person identification.
Biometric systems also introduce an aspect of user convenience; it means one can be authorized by representing
himself or herself. In this paper, the main focus is on working principal of biometric technique, the various
biometrics systems and their comparisons.
Keywords: Biometrics, authentication, identification, recognition
FEATURE EXTRACTION METHODS FOR IRIS RECOGNITION SYSTEM: A SURVEYijcsit
This document summarizes several feature extraction methods for iris recognition systems. It discusses supervised, unsupervised, and semi-supervised learning approaches for iris recognition. It also reviews related literature on iris recognition techniques, including using wavelet transforms, SVM classifiers, and other feature extraction methods. Tables in the document compare different biometric traits and traditional biometric systems, as well as summarize reviewed articles on iris recognition with their main contributions. The methodology section describes the typical four steps of an iris recognition system: image acquisition, preprocessing, feature extraction, and matching/recognition. It also discusses various iris recognition methods and their performance measures.
Advanced Authentication Scheme using Multimodal Biometric SchemeEditor IJCATR
This document presents a study on using multimodal biometrics with palm and fingerprint recognition to improve identification accuracy. The authors first discuss existing unimodal biometrics and limitations. They then describe the typical steps in a multimodal system: image capture, preprocessing, feature extraction, fusion, and matching. For this study, minutiae extraction is used to extract fingerprint features while local binary patterns extract palm features. Wavelet fusion is applied to the extracted features before support vector machine matching. The authors aim to demonstrate that combining palm and fingerprint biometrics can achieve better performance than single biometrics alone.
This document proposes a system for strengthening security for online banking transactions. It involves multi-level authentication including face recognition, graphical OTP authentication using a 4x4 grid of random numbers, and security questions. Users first register security images, a security pattern by selecting indexes on a 4x4 grid, answers to security questions, and their face is recorded. For login, the security images and username/password are verified. Transactions require face recognition if a webcam is available, otherwise graphical OTP authentication is used where the user selects numbers from the indexes of their security pattern on a randomly generated 4x4 grid. Additionally, two random security questions are asked before completing a transaction. The system aims to provide secure electronic transactions through this multi-factor
Pre-Processing Image Algorithm for Fingerprint Recognition and its Implementa...ijseajournal
This document discusses a pre-processing image algorithm for fingerprint recognition and its implementation on a DSP TMS320C6416. It first presents the pre-processing steps used to improve fingerprint image quality, such as grayscale transformation, normalization, segmentation, and Gabor filtering. It then discusses implementing the algorithm on the TMS320C6416 DSP hardware platform, which features a 600MHz processor, internal and external memory, and cache memories. The DSP platform allows for fast, powerful image processing needed for real-time fingerprint recognition applications.
This document proposes a grid-based feature extraction method for offline signature verification. It begins with an introduction and discusses existing techniques and their limitations. It then presents the proposed work, which involves signature acquisition, preprocessing, feature extraction by segmenting the signature image into a grid, and verification. The algorithms, mathematical model, advantages and applications are described. The document concludes that the proposed method requires only low-cost hardware and has a low error rate for signature verification.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
PREPROCESSING ALGORITHM FOR DIGITAL FINGERPRINT IMAGE RECOGNITION ijcsity
Biometrics is one of the most used technologies in the field of security due to its reliability and
performance. It is based on several physical human characteristics but the most used technology is the
fingerprint recognition, and since we must carry out an image processing to be able to exploit the data in
each fingerprint we propose in this article an image preprocessing procedure in order to improve its
quality before extracting the necessary information for the comparison phase.
A SURVEY ON DEEP LEARNING METHOD USED FOR CHARACTER RECOGNITIONIJCIRAS Journal
The field of Artificial Intelligence is very fashionable today, especially neural networks that work well in various areas such as speech recognition and natural language processing. This Research Article briefly describes how deep learning models work and what different techniques are used in text recognition. It also describes the great progress that has been made in the field of medicine, the analysis of forensic documents, the recognition of license plates, banking, health and the legal industry. The recognition of handwritten characters is one of the research areas in the field of artificial intelligence. The individual character recognition has a higher recognition accuracy than the complete word recognition. The new method for categorizing Freeman strings is presented using four connectivity events and eight connectivity events with a deep learning approach.
A Smart Receptionist Implementing Facial Recognition and Voice InteractionCSCJournals
The purpose of this research is to implement a smart receptionist system with facial recognition and voice interaction using deep learning. The facial recognition component is implemented using real time image processing techniques, and it can be used to learn new faces as well as detect and recognize existing faces. The first time a customer uses this system, it will take the person’s facial data to create a unique user facial model, and this model will be triggered if the person comes the second time. The recognition is done in real time and after which voice interaction will be applied. Voice interaction is used to provide a life-like human communication and improve user experience. Our proposed smart receptionist system could be integrated into the self check-in kiosks deployed in hospitals or smart buildings to streamline the user recognition process and provide customized user interactions. This system could also be used in smart home environment where smart cameras have been deployed and voice assistants are in place.
The document is a research paper that studies using a neural network model for fingerprint recognition. It discusses how fingerprint recognition is an important technique for security and restricting intruders. The paper proposes using an artificial neural network with backpropagation training to recognize fingerprints. It describes collecting fingerprint images, classifying them, enhancing the images, and training the neural network to match images and recognize fingerprints with high accuracy. The methodology, implementation, and results of using a backpropagation neural network for fingerprint recognition are analyzed.
Biometric system is a pattern identification system that recognizes an individual by determining the originality of the physical features and behavioral characteristic of that person. Of all the recently used biometric techniques, fingerprint identification systems have gained the most popularity because of the prolonged existence of fingerprints and its extensive use. Fingerprint is dependable biometric trait as it is an idiosyncratic and dedicated. It is a technology that is increasingly used in various fields like forensics and security purpose. The vital objective of our system is to make ATM transaction more secure and user friendly. This system replaces traditional ATM cards with fingerprint. Therefore, there is no need to carry ATM cards to perform transactions. The money transaction can be made more secure without worrying about the card to be lost. In our system we are using embedded system with biometrics i.e r305 sensor and UART microcontroller. The Fingerprint and the user_id of all users are stored in the database. Fingerprints are used to identify whether the Person is genuine. A Fingerprint scanner is used to acquire the fingerprint of the individual, after which the system requests for the PIN (Personal Identification Number). The user gets three chances to get him authenticated. If the fingerprints do not match further authentication will be needed. After the verification with the data stored in the system database, the user is allowed to make transactions.
IRIS Recognition Based Authentication System In ATMIJTET Journal
Security and Authentication of individuals is necessary for our daily lives especially in ATMs. It has been improved by using biometric verification techniques like face recognition, fingerprints, voice and other traits, comparing these existing traits, there is still need for considerable computer vision. Iris recognition is a particular type of biometric system that can be used to reliably identify a person uniquely by analyzing the patterns found in the iris. Initially Iris images are collected as datasets and maintained in agent memory. Then the Iris and pupil are detected from the image, removing noises. The features of the iris were encoded by convolving the normalized iris region with 2DGabor filter. The Hamming distance was chosen as a matching metric, which gave the measure of how many bits disagreed between the templates of the iris.
IRJET - An Enhanced Signature Verification System using KNNIRJET Journal
This document proposes an enhanced signature verification system using K-nearest neighbors (KNN) classification. It discusses how signature verification aims to automatically determine if a biometric sample matches a claimed identity. The proposed system extracts features from signatures and uses KNN to classify signatures as genuine or forgeries. It also reviews related work on signature verification using techniques like artificial immune systems and discusses preprocessing steps like normalization to standardize signature size and reduce variations between signatures.
Integration of Machine Learning in attendance and payrollAkshat Gupta
Anisha Kundu (Author) & Akshat Gupta (Co-Author)
In recent times, machine learning has become one of the key aspects of data handling. After years of research by the scientists, neuroscientists, and psychologists, numerous feasible technologies are available; some credit may go to the commercial and law enforcement applications as well. This paper proposes a technique for biometric recognition, which analyzes the geometry of the hand to find and isolate the vein patterns from near-infrared palm and wrist images and extract features based on repeated line tracking algorithm and maximum curvature algorithm.
Fingerprint Authentication Using Biometric And Aadhar Card FingerprintSonuSawant
The document provides information about fingerprint authentication. It discusses how fingerprint authentication works by verifying a match between a captured fingerprint and one stored in a database. The fingerprint authentication process involves fingerprint capture, pre-processing, feature extraction, and matching. It notes that fingerprint authentication is widely used for security access control and online transactions due to fingerprints being unique and unchanging throughout a person's lifetime.
Utilization of Machine Learning in Computer VisionIRJET Journal
The document discusses the utilization of machine learning in computer vision. It begins by defining machine learning and computer vision, noting they aim to bring human data sensing and understanding capabilities to computers. It then discusses several applications of machine learning in computer vision, such as object detection in images using algorithms like convolutional neural networks. Finally, it concludes that machine learning and computer vision have reduced costs and improved technologies in many fields like healthcare, transportation and more, with emerging areas including life sciences and human activity analysis.
IRJET- Eye Tracking for Password Authentication using Machine LearningIRJET Journal
This document presents an eye tracking system for password authentication using machine learning. It aims to overcome shoulder surfing attacks by allowing users to enter passwords using their eye movements instead of a keyboard. The system detects the user's eye pupil location using a Haar cascade algorithm and measures the distance between the eye center and pupil to determine if the user is looking left, right, or center. Numbers are displayed on screen and the user selects them by focusing on them with their eyes. The entered password is compared to a trained dataset and access is allowed only if it matches. This gaze-based authentication method leaves no trace of the password and makes it difficult for observers to steal authentication information through shoulder surfing.
Facial Recognition based Attendance System: A SurveyIRJET Journal
The document describes a facial recognition-based attendance system. It discusses how traditional attendance methods are inefficient and error-prone. The proposed system utilizes facial recognition technology, machine learning algorithms, and a database to accurately identify and track attendance in real-time. It analyzes different facial recognition and machine learning methods like OpenCV, cosine similarity, and distance metrics to efficiently and securely match facial templates. The system aims to provide a customized, user-friendly and robust alternative to traditional attendance tracking methods in educational institutions and organizations.
Real Time Vision Hand Gesture Recognition Based Media Control via LAN & Wirel...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Graphical password based hybrid authentication system for smart hand held dev...Alexander Decker
The document proposes a new hybrid graphical password scheme for authentication on smart handheld devices. It combines recognition and recall-based techniques. During registration, the user selects objects as a graphical password and assigns digits to each object. For authentication, the user selects the objects in order and enters the corresponding digits. The scheme aims to improve usability and security over text passwords while addressing issues like shoulder surfing that graphical passwords often face. It is designed for smart devices like phones which are more convenient than desktop computers.
Network security is enhanced through biometrics authentication which uses unique physical traits to verify user identity. Biometrics is more secure than passwords since traits cannot be forgotten, stolen, or easily copied. The document discusses common biometric traits like fingerprints, iris scans, and voice recognition. It explains how biometric systems work by enrolling traits during initial use then comparing submitted traits to stored information for authentication. Biometrics provides stronger security for networks and systems by using the human body as a verification method.
This document discusses fingerprint recognition. It begins by defining fingerprint recognition as the automated process of verifying a match between two fingerprints. Fingerprints are a form of biometrics used to identify individuals due to their uniqueness. The document then discusses how fingerprints are distinguished by features called minutiae, specifically ridge endings and bifurcations. It also outlines some common fingerprint matching techniques such as correlation-based and minutiae-based matching.
AI Approach for Iris Biometric Recognition Using a Median FilterNIDHI SHARMA
The Artificial Intelligence approach is used for Iris recognition by understanding the distinctive and measurable characteristics of the human body such as a person’s face, iris, DNA, fingerprints, etc. AI methods analyzed the attributes like iris images. Privacy and Security being a major concern nowadays, Recognition Technique can find numerous applications.
This document proposes a centralized biometric voting system using fingerprint recognition. It discusses how fingerprint scanners work by scanning fingerprints and comparing them to a centralized database. The proposed system aims to improve security, reduce fake voting, and allow voters to cast their ballot from anywhere by authenticating through fingerprint biometrics. It analyzes the technical, economic, and operational feasibility of the system. The results suggest it improves the current voting process by making it more reliable, secure, and reducing required manpower through automation. The system aims to maximize voter participation using a centralized database for authentication.
This document summarizes research on offline and online signature verification systems. For offline signature verification, the document discusses common feature extraction techniques like projection, point density, fractal dimension, and classifiers like SVM, neural networks. Accuracy rates from various studies ranging from 78% to 97% are provided. For online signature verification, the document discusses features extraction methods like DTW and classifiers like HMM, ANN. Accuracy rates from different studies ranging from 0% to 21.5% FRR and 0% to 5% FAR are also presented. The document concludes that signature verification is still an open problem and combining foreground and background information could provide better results.
1. The document discusses how biometrics can enhance network security by providing unique authentication through physical traits like fingerprints, iris scans, and voice patterns.
2. Biometric systems work by enrolling users through capturing traits, storing trait data, and comparing new trait inputs to what is on file for authentication.
3. Common biometric technologies discussed are fingerprints, iris scanning, handwriting analysis, voiceprints, vein patterns, which can all uniquely identify individuals for security purposes. The document argues that biometrics provide more secure authentication than passwords.
This document summarizes a research paper on implementing a fingerprint-based biometric authentication system for ATMs using a PIC microcontroller. It describes how fingerprint identification works by analyzing ridge and valley patterns. The system uses a PIC16F877A microcontroller to collect fingerprint data from a fingerprint sensor module and match it to an enrolled fingerprint template to authenticate users. If a match is found, the ATM cashbox opens, and if not, an alarm sounds. The document discusses the methodology, advantages, limitations and components of the system, including the fingerprint sensor, microcontroller, LCD display, motor driver, and buzzer.
Similar to Computer vision approaches for offline signature verification & forgery detection a survey (20)
Performance of Wideband Mobile Channel with Perfect Synchronism BPSK vs QPSK ...Editor Jacotech
Direct-sequence code-division multiple access (DS-CDMA) is
currently the subject of much research as it is a promising
multiple access capability for third and fourth generations
mobile communication systems. The synchronous DS-CDMA
system is well known for eliminating the effects of multiple
access interference (MAI) which limits the capacity and
degrades the BER performance of the system. In this paper,
we investigate the bit error rate (BER) performance of a
synchronous DS-CDMA system over a wideband mobile
radio channel. The BER performance is affected by the
difference in path length ΔL and the number of arriving
signals N. Furthermore, the effect of these parameters is
examined on the synchronous DS-CDMA system for different
users’ number as well as different processing gain Gp. In this
environment and under the above conditions the performances
of the BPSK (Binary Phase Shift Keying) and the QPSK
(Quadrature Phase Shift Keying) modulations are compared.
The promising simulation results showed the possibility of
applying this system to the wideband mobile radio channel.
MOVIE RATING PREDICTION BASED ON TWITTER SENTIMENT ANALYSISEditor Jacotech
With microblogging platforms such as Twitter generating
huge amounts of textual data every day, the possibilities of
knowledge discovery through Twitter data becomes
increasingly relevant. Similar to the public voting mechanism
on websites such as the Internet Movie Database (IMDb) that
aggregates movies ratings, Twitter content contains
reflections of public opinion about movies. This study aims to
explore the use of Twitter content as textual data for
predicting the movie rating. In this study, we extract number
of tweets and compiled to predict the rating scores of newly
released movies. Predictions were done with the algorithms,
exploring the tweet polarity. In addition, this study explores
the use of several different kinds of tweet classification
Algorithm and movie rating algorithm. Results show that
movie rating developed by our application is compared to
IMDB and Rotten Tomatoes.
Non integer order controller based robust performance analysis of a conical t...Editor Jacotech
The design of robust controller for any non linear process is a
challenging task because of the presence of various types of
uncertainties. In this paper, various design methods of robust
PID controller for the level control of conical tank are
discussed. Uncertainties are of different types, among that
structured uncertainty of 30% is introduced to the nominal
plant for analysing the robustness. As a first step, the control
of level is done by using conventional integer order controller
for both nominal and uncertain system. Then, the control is
done by means of Fractional Order Proportional Integral
Derivative (FOPID) controller for achieving robustness. With
the help of time series parameters, a comparison is made
between conventional PID and FOPID with respect to the
simulated output using MATLAB and also analyzed the
robustness.
FACTORS CAUSING STRESS AMONG FEMALE DOCTORS (A COMPARATIVE STUDY BETWEEN SELE...Editor Jacotech
This document summarizes a research study that examined factors causing stress among female doctors working in public and private sector hospitals in India. The study aimed to identify whether there were associations between hospital sector (public or private) and 12 different stress measures among 300 female doctors. A survey was administered to collect data. Chi-square tests found statistically significant associations (p < 0.05) between hospital sector and 11 of the 12 stress measures, including stress due to workload, working conditions, physical exertion, emotional exhaustion, job security, organizational support, work-family conflict, family adjustment, task demands, patient expectations, and working hours. Only the association between sector and stress due to psychosomatic problems was not statistically significant. The results indicate
ANALYSIS AND DESIGN OF MULTIPLE WATERMARKING IN A VIDEO FOR AUTHENTICATION AN...Editor Jacotech
Watermarking technique be employ instance & for a second time for
validation and protection of digital data (images, video and audio
files, digital repositories and libraries, web publishing). It is helpful
to copyright protection and illegal copying of digital data like video
frames and making digital data more robust and imperceptible. With
the advent of internet, creation and delivery of digital data has grown
many fold. In that Scenario has to need a technique for transferring
digital data securely without changing their originality and
robustness. In this paper proposed a plan of latest watermarking
method which involves inserting and adding two or more digital data
or pictures in a single video frame for the principle of protection and
replicate the similar procedure for N no video frames for
authentication of entire digital video. After that digital video is
encrypted and decrypted by using motion vector bit-xor encryption
and decryption technique.
The Impact of Line Resistance on the Performance of Controllable Series Compe...Editor Jacotech
In recent years controllable FACTS devices are increasingly
integrated into the transmission system. FACTS devices that
provide series control such as Controllable Series Compensator
(CSC) has significant effect on the voltage stability of Electric
Power system. In this work impact of line resistance on the
performance of CSC in a single-load infinitive-bus (SLIB)
model is investigated. The proposed framework is applied to
SLIB model and obtained results demonstrates that line
resistance has considerable effect on voltage stability limits and
performance of CSC.
Security Strength Evaluation of Some Chaos Based Substitution-BoxesEditor Jacotech
Recently, handful amount of S-boxes, using the various
methods such as affine transformations, gray coding,
optimization, chaotic systems, etc, have been suggested. It is
prudent to use cryptographically strong S-boxes for the design
of powerful ciphers. In this paper, we sampled some widely
used 8×8 S-boxes which are recently synthesized and security
analysis and evaluation is executed to uncover the best
candidate(s). The performance analysis is exercised against
the crucial measures like nonlinearity, linear approximation
probability, algebraic immunity, algebraic complexity,
differential uniformity. These parameters are custom selected
because their scores decide the security strength against
cryptographic assaults like linear cryptanalysis, algebraic
attacks, and differential cryptanalysis. The anticipated
analysis in this work facilitates the cryptographers, designers,
researchers to choose suitable candidate decided over many
parameters and can be engaged in modern block encryption
systems that solely rely on 8×8 S-box. Moreover, the analysis
assists in articulating efficient S-boxes and to evaluate the
attacks resistivity of their S-boxes.
Traffic Detection System is an Android application that aims at determining the behavior of traffic in a particular location. It calculates the speed of the vehicle and the level of congestion or the amount of traffic is determined on the basis of the values of sensors. If any such obstruct found, then the driver is provided an option to send messages regarding high traffic to his/her friends. After a distinct number of repeated low speed and breaks, the location of the vehicle (latitude and longitude) send to a pre-specified contact (selected in case of traffic congestion) through an SMS. This application uses the features of the Global positioning system. The Latitude, as well as the longitude of the location where traffic jams are formed, is sent to the friends of the user. The Goggle map of the location also sends to the friends. It uses the SMS Manager a functionality of Android. The friends receiving the messages will thereby avoid taking the congested route and hence the level of traffic on the congested road will decrease, and the friends will reach the destination in comparatively less time.
Performance analysis of aodv with the constraints of varying terrain area and...Editor Jacotech
Mobile Ad Hoc Networks (MANETs) are wireless networks,
where there is no requirement for any infrastructure support to
transfer data packets between mobile nodes. These nodes
communicate in a multi-hop mode; each mobile node acts
both as a host and router. The main job of Quality of Service
(QoS)[1][2] routing in MANETs is to search and establish
routes among different mobile nodes for satisfying QoS
requirements of wireless sensor networks as PDR, Average
end-to-end delay, Average Throughput. The QoS routing
protocols efficient for commercial, real-time and multimedia
applications are in demand for day to day activities[2].
Modeling of solar array and analyze the current transient response of shunt s...Editor Jacotech
Spacecraft bus voltage is regulated by power
conditioning unit using switching shunt voltage regulator having
solar array cells as the primary source of power. This source
switches between the bus loads and the shunt switch for fine
control of spacecraft bus voltage. The effect of solar array cell
capacitance [5][6] along with inductance and resistance of the
interface wires between solar cells and power conditioning
unit[1], generates damped sinusoidal currents superimposed on
the short circuit current of solar cell when shunted through
switch. The peak current stress on the shunt switch is to be
considered in the selection of shunt switch in power conditioning
unit. The analysis of current transients of shunt switch in PCU
considering actual spacecraft interface wire length by
illumination of solar panel (combination of series and parallel
solar cells) is difficult with hardware simulation. Software
simulation by modeling solar cell is carried out for a single string
(one parallel) in Pspice [6]. Since in spacecrafts number of
parallels and interface cable length are variable parameters the
analysis of current transients of shunt switch is carried out by
modeling solar array with the help of solar cell model[6] for the
actual spacecraft condition.
License plate recognition an insight to the proposed approach for plate local...Editor Jacotech
License Plate Recognition (LPR) system for vehicles is an innovative and a very challenging area for research due to the innumerous plate formats and the nonuniform outdoor illumination conditions during which images are acquired. Thus, most approaches developed, work under certain restrictions such as fixed illumination, stationary background and limited speed. Algorithms developed for LPR systems are generally composed of three significant stages: 1] localization of the license plate from an entire scene image; 2] segmentation of the characters on the plate; 3] recognition of each of the segmented characters. A simple approach for preprocessing of the images, localization and extraction phase has been described in this paper. Numerous procedures have been developed for LPR systems and are assessed in this paper taking into consideration issues like processing time, computational power and recognition rate wherever available.
Design of airfoil using backpropagation training with mixed approachEditor Jacotech
Levenberg-Marquardt back-propagation training method has some limitations associated with over fitting and local optimum problems. Here, we proposed a new algorithm to increase the convergence speed of Backpropagation learning to design the airfoil. The aerodynamic force coefficients corresponding to series of airfoil are stored in a database along with the airfoil coordinates. A feedforward neural network is created with aerodynamic coefficient as input to produce the airfoil coordinates as output. In the proposed algorithm, for output layer, we used the cost function having linear & nonlinear error terms then for the hidden layer, we used steepest descent cost function. Results indicate that this mixed approach greatly enhances the training of artificial neural network and may accurately predict airfoil profile.
Ant colony optimization based routing algorithm in various wireless sensor ne...Editor Jacotech
Wireless Sensor Network has several issues and challenges due to limited battery backup, limited computation capability, and limited computation capability. These issues and challenges must be taken care while designing the algorithms to increase the Network lifetime of WSN. Routing, the act of moving information across an internet world from a source to a destination is one of the vital issue associated with Wireless Sensor Network. The Ant Colony Optimization (ACO) algorithm is a probabilistic technique for solving computational problems that can be used to find optimal paths through graphs. The short route will be increasingly enhanced therefore become more attractive. The foraging behavior and optimal route finding capability of ants can be the inspiration for ACO based algorithm in WSN. The nature of ants is to wander randomly in search of food from their nest. While moving, ants lay down a pheromone trail on the ground. This chemical pheromone has the ability to evaporate with the time. Ants have the ability to smell pheromone. When selecting their path, they tend to select, probably the paths that has strong pheromone concentrations. As soon as an ant finds a food source, carries some of it back to the nest. While returning, the quantity of chemical pheromone that an ant lay down on the ground may depend on the quantity and quality of the food. The pheromone trails will lead other ants towards the food source. The path which has the strongest pheromone concentration is followed by the ant which is the shortest paths between their nest and food source. This paper surveys the ACO based routing in various Networking domains like Wireless Sensor Networks and Mobile Ad Hoc Networks.
An efficient ant optimized multipath routing in wireless sensor networkEditor Jacotech
Today, the Wireless Sensor Network is increasingly gaining popularity and importance. It is the more interesting and stimulating area of research. Now, the WSN is applied in object tracking and environmental monitoring applications. This paper presents the self-optimized model of multipath routing algorithm for WSN which considers definite parameters like delay, throughput level and loss and generates the outcomes that maximizes data throughput rate and minimizes delay and loss. This algorithm is based on ANT optimization technique that will bring out an optimal and organized route for WSN and is also to avoid congestion in WSN, the algorithm incorporate multipath capability..
A mobile monitoring and alert sms system with remote configuration – a case s...Editor Jacotech
One of the parent´s main concerns nowadays it to know their children´s whereabouts. Some applications exist to address this issue and most of them rely on internet connection which makes the solution expensive. In this paper we present a low cost solution, based on SMS, and with the ability to remotely configure the child monitoring process. We also present the architecture and the full flowchart of the child application whenever a SMS is received. This case study uses Android and the more recent location API – the Fused Location Provider. For obvious reasons, the security issue has been a concern, which resulted in a configuration module in the child application to specify authorized senders
Leader Election Approach: A Comparison and SurveyEditor Jacotech
In distributed system, the coordinator is needed to manage the use of the resources in the shared environment. Many algorithms have been proposed for the same. They have various positive and negative parts. Here we will discuss those issues which ensure the efficiency of the algorithm for election leader. Here a comparison will be provided to show the advantages and disadvantages of different election algorithms. The comparison would be based on the number of messages passing and the order of time complexity.
Leader election approach a comparison and surveyEditor Jacotech
This document summarizes and compares several leader election algorithms in distributed systems. It discusses the Bully algorithm and some modifications, including using two successors, dividing nodes into sets, and using max-heap and Fibonacci heap data structures. The algorithms are compared based on time complexity, number of messages required, and memory usage. The Fibonacci heap approach is identified as the most efficient with O(log n) time complexity and minimum message passing of log(n).
Modeling of solar array and analyze the current transientEditor Jacotech
Spacecraft bus voltage is regulated by power
conditioning unit using switching shunt voltage regulator having
solar array cells as the primary source of power. This source
switches between the bus loads and the shunt switch for fine
control of spacecraft bus voltage. The effect of solar array cell
capacitance [5][6] along with inductance and resistance of the
interface wires between solar cells and power conditioning
unit[1], generates damped sinusoidal currents superimposed on
the short circuit current of solar cell when shunted through
switch. The peak current stress on the shunt switch is to be
considered in the selection of shunt switch in power conditioning
unit. The analysis of current transients of shunt switch in PCU
considering actual spacecraft interface wire length by
illumination of solar panel (combination of series and parallel
solar cells) is difficult with hardware simulation. Software
simulation by modeling solar cell is carried out for a single string
(one parallel) in Pspice [6]. Since in spacecrafts number of
parallels and interface cable length are variable parameters the
analysis of current transients of shunt switch is carried out by
modeling solar array with the help of solar cell model[6] for the
actual spacecraft condition.
Traffic Detection System is an Android application that aims at determining the behavior of traffic in a particular location. It calculates the speed of the vehicle and the level of congestion or the amount of traffic is determined on the basis of the values of sensors. If any such obstruct found, then the driver is provided an option to send messages regarding high traffic to his/her friends. After a distinct number of repeated low speed and breaks, the location of the vehicle (latitude and longitude) send to a pre-specified contact (selected in case of traffic congestion) through an SMS. This application uses the features of the Global positioning system. The Latitude, as well as the longitude of the location where traffic jams are formed, is sent to the friends of the user. The Goggle map of the location also sends to the friends. It uses the SMS Manager a functionality of Android. The friends receiving the messages will thereby avoid taking the congested route and hence the level of traffic on the congested road will decrease, and the friends will reach the destination in comparatively less time.
Performance analysis of aodv with the constraints ofEditor Jacotech
This document summarizes a research paper that analyzed the performance of the AODV routing protocol in wireless sensor networks under different terrain area sizes and pause times using the NS-3 simulator. The researchers found that packet delivery ratio remained nearly constant for small terrain areas but decreased for larger areas. Average throughput decreased with larger terrain areas, while average delay remained nearly constant for small areas but increased for larger ones. The paper concludes that AODV has better performance in networks with high mobility and size and is preferred for real-time traffic over other protocols like DSR and DSDV.
Performance analysis of aodv with the constraints of
Computer vision approaches for offline signature verification & forgery detection a survey
1. Journal of Advanced Computing and Communication Technologies (ISSN: 2347 - 2804)
Volume No.2Issue No. 4, August 2014
(ETACICT-2014)
37
Computer Vision Approaches for Offline Signature Verification & Forgery Detection: A Survey By
Gautam. S. Prakash, Shanu Sharma Student, CSE Department, ASET, Amity University, Noida,Uttar Pradesh, India Assistant Professor, CSE Department, ASET, Amity University Noida,Uttar Pradesh, India
gautamsprakash@gmail.com , shanu.sharma1611@gmail.com
ABSTRACT Automated signature verification and forgery detection has many applications in the field of Bank-cheque processing, document authentication. ATM access etc. Handwritten signatures have proved to be important in authenticating a person's identity, who is signing the document. In this paper, reviews of previous studies and systems to verify signatures and detect forgery is provided and analyzed. Brief summary of computer vision techniques are presented to automate the process. Also, the important features and shortcomings of these systems and studies in this field are summarized in this paper. Keywords Forgery detection, Signature verification, Artificial Neural Network (ANN), Fuzzy Logic, Computer Vision. 1. Introduction Forgery is a process by which, identity documents of a person are copied or modified by such a person who is not authorized to do so, or are involved in modification, for the purpose of deceiving others. Signature, from the Latin word "Signare" meaning "Sign" is a stylized handwritten representation of a person's name or an identification mark that a person writes on documents/texts. For many centuries, signatures have been used as an important element in authentication of any person's identity, who is signing the document. The unique characteristics of a person's signature represents the person's identity and the person's consent for the terms of the document/text. The field of signature authentication is very important and hence the problem of verification and forgery detection is of the utmost importance. Handwritten stylized signatures vary largely from person to person. They differ in their sizes and shapes, and the variations are so much, that for a human being, just by having a glance at the signature, it is very difficult to separate out a genuine signature from a one that is forged. An automatic signature verification system can either be online or offline. In an online verification system, as the person signs the document/text, the person's signatures are recorded. The merit of such a system is that, a person's dynamic information characteristics can also be accounted. But the problem with such a system is that, in reality, most of the documents are already pre-signed. Hence to deal with such situations, an offline verification system is used, which only accounts for the static features of a signature.
Image Processing has found number of applications in the field of forensic examination. Image processing has proved to be very effective tool to analyze thousands of signatures in the database, and apply techniques for detailed analysis such as fuzzy logic and artificial neural network to decrease the amount of time, and increase the effectiveness of the system. For better understanding of further studies, it is important to be acquainted with the basic common concepts such as computer vision technology, and the need for automated signature verification. A brief explanation about them are given below. 1.1. Computer Vision Technology Computer Vision Technology is used for automating the vision perception process. Computer vision is a field that includes methods for acquiring, processing, analyzing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions. Computer vision covers the core technology of automated image analysis which is used in many fields. As a scientific discipline, computer vision is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences, views from multiple cameras, or multi-dimensional data from a medical scanner. As a technological discipline, computer vision seeks to apply its theories and models to the construction of computer vision systems. 1.2. Need For Automated Signature Verification Signature verification is very important in realizing tele- banking and tele-networking systems, where signatures can be used to identify and authenticate a subscriber. An automated verification process would enable banks and other financial institutions to significantly reduce check and money order forgeries, which account for a large monetary loss each year. Reliable signature verification can be of great help in many other application areas such as law enforcement, industry, security control and so on. Handwritten signatures appear on many types of documents such as bank checks and credit slip etc. The large volume of such documents makes automatic signature verification desirable. A system for signature verification requires high reliability.
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2. Review of Computer Vision and Soft Computing techniques for Offline Signature Verification & Forgery Detection The problem of signature verification and forgery detection of documents ha long been an interest field in the field of image processing. Many studies have been done till now in order to develop offline signature verification systems using computer vision technology and soft computing techniques. Many researchers are still working on design, development and implementation of an automatic system for fast and much more effective as well as reliable signature verification system. 2.1. Computer Vision Technology Computer vision is described as automation and integration of a wide range of processes and representations for vision perception. Images can be formed by the system for perception by a range of physical devices, which can include still and video cameras, x-ray devices, electron microscopes, radar, and ultrasound, and used for several purposes, including entertainment, medical, business, industrial, military, civil, security, and scientific. For each case the aim is for an observer, human or machine, to excerpt essential information about the scene being imaged. Computer vision, in some ways, is the inverse of computer graphics as computer graphics produces image data from 3D models, computer vision often produces 3D models from the image data. 2.2 Digital Image Processing Digital image processing refers to the use of computer algorithms in order to perform image processing on digital images. Through this image processing, one aims to enhance the features of the image that are of interest, while removing the details which are irrelevant to the given application, and then extract the vital information from the enhanced image. The operations of image processing can be divided broadly into three categories, Image Compression, Image Enhancement and Restoration, and Measurement Extraction. Defects in images which could be a result of the digitization process or faults in the imaging set-up (for example, bad lighting & image noise) can be rectified by using Image Enhancement techniques. As soon as the image is in a good condition, the Measurement Extraction operations can be utilized to obtain essential information from the image. 2.3. Soft Computing Soft Computing refers to a collection of various techniques which uses human mind to formalize cognitive processes. It basically is a term used to refer to the problems whose solutions are unpredictable, uncertain and lies between 0 and 1. It deals with imprecision, uncertainty, partial truth, and approximation to achieve practicability, robustness and low solution costs. 2.4. Soft Computing Techniques 2.4.1. Fuzzy Logic
Fuzzy logic is relatively young theory. Major advantage of this theory is that it allows the natural description, in linguistic terms, of problems that should be solved rather than in terms of relationships between precise numerical values. This advantage, dealing with the complicated systems in simple way, is the main reason why fuzzy logic theory is widely applied in technique. Using Fuzzy Logic it is also possible to classify the remotely sensed image (as well as any other digital imagery). Fuzzy logic is a form of many-valued logic. It deals with reasoning that is approximate rather than fixed and exact. Compared to traditional binary sets (where variables may take on true or false values) fuzzy logic variables may have a truth value that ranges in degree between 0 and 1. Fuzzy logic has been extended to handle the concept of partial truth, where the truth value may range between completely true and completely false. Furthermore, when linguistic variables are used, these degrees may be managed by specific functions. Irrationality can be described in terms of what is known as the fuzzjective. 2.4.2. Artificial Neural Networks (ANNs) In computer science and related fields, artificial neural networks are computational models inspired by animal central nervous systems (in particular the brain) that are capable of machine learning and pattern recognition. They are usually presented as systems of interconnected "neurons" that can compute values from inputs by feeding information through the network. For example, in a neural network for handwriting recognition, a set of input neurons may be activated by the pixels of an input image representing a letter or digit. The activations of these neurons are then passed on, weighted and transformed by some function determined by the network's designer, to other neurons, etc., until finally an output neuron is activated that determines which character was read. Like other machine learning methods, neural networks have been used to solve a wide variety of tasks that are hard to solve using ordinary rule-based programming, including computer vision and speech recognition. For any research work, the literatures are very helpful for the researchers to motivate for the innovation of new ideas for more fruitful results. Till now, researchers have proposed numerous features extraction and classification techniques based on image processing techniques and different classification algorithms. These are the literature surveys regarding the digital image processing in this particular field. By taking the help of these types of researches new research work is evolving in image processing field with the work. 2.5. Related Systems
Md. Iqbal Quraishi et al. [1] have proposed in their paper an Artificial Neural Network approach which implements an Automated Signature Verification and Authentication system. Their method comprises of various transformation techniques from the spatial as well as frequency domain. It also implements the use of Riplet-II transformation to extract the region of interest. To enhance the image, further it implements the use of Log Polar Transformation. They have implemented a Feed Forward Back Propagation Neural Network for the verification and authentication. They have considered 30 neurons in the hidden layer of the ANN The system proposed by the authors, has the accuracy of 96.15%, with the forgery detection rate of 92%. The False Acceptance Rate (FAR) is found to be 5.28%, and False Rejection Rate (FRR) of 2.56%. The authors have compared their system with other existing system and have found that their proposed system has better performance as compared to others. The drawback is that the test needs to be trained before the implementation, which is
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time consuming. There can be further improvement is the system with better performance rates. Othman o-khalifa, Md. Khorshed Alam et al. [2] have reviewed offline signature verification schemes in their paper. They have considered the Artificial Neural Network Technique, and have compared various offline signature verification approaches and their issues. For the pre- processing of the data acquired the have used techniques such as Background Elimination, Noise Reduction, Thinning and Width Normalization. For the purpose of feature extraction, they have considered the global, geometric, texture, mask and grid features. They have explained how the ANN approach works in the signature Verification and what steps are involved. The authors have also pointed out that the main concern of the signature verification system is to provide the high security to access any confidential things those are highly restricted. Rameez Wajid et al. [3] have evaluated the performance of various classifiers for offline signature verification based upon the local binary patterns (LBP) feature set. They have performed the feature vector by dividing the signature images into twelve local regions and forming a code matrix by their LBPs. The authors have investigated the performance of seven classifiers on The FUM-Persian Handwritten Signature Database (FUM-PHSDB) comprising of 20 classes of genuine and forged signatures of depth 20 and 10 respectively. The classifiers considered by them are Support vector Machines(SVM), Least Squares-Support Vector Machines (LS-SVM), Distance Likelihood ratio Test (DLRT), Artificial Neural Network (ANN), Fisher's Linear Discriminant (FLD), Logistics Discriminant and Naive Bayes. Their experimental findings depict that LS-SVM performs the best among the seven classifiers, achieving the Equal Error Rate (EER) of 13%. Muhammad Imran Malik et al. [4] have evaluated the impact of two state of the art offline signature verification systems which are based on local and global features respectively. The authors have investigate the performance of automated systems on disguised signatures. The systems were evaluated upon the publically available datasets from signature verification competition. The ICDAR 2009 Offline Signature Verification Competition dataset and the ICFHR 2010 4NSignComp datasets were considered. The offline signature verification systems considered for evaluation were Local Features combined with Gaussian Mixture Models (GMMs) and Global Features combined with k-Nearest Neighbour (kNN). In their experiments it was observed that global features are capable of providing good results if only a detection of genuine and forged signatures is needed. Local features are much better suited to solve the forensic signature verification cases when disguised signatures are also involved.
Juan Hu et al. [5] have presented an offline signature verification system using three different pseudo-dynamic features, two different classifier training approaches and two datasets. Three separate pseudo-dynamic features based on gray level: Local Binary Pattern (LBP), Gray Level Co- occurrence Matrix (GLCM) and Histogram Oriented Gradients (HOG) have been used. The classification is performed using the wrier dependent Support Vector Machine (SVMs) classifier and Global Real Adaboost method. In their experiments, the results of the Equal Error Rate (EER) of skilled forgery test using the writer-dependent approach obtained were 11.73% for LBP, 11.54% for GLCM and 9.83% for HOG. The combination of the three resulted in EER of 7.66%. The results of EER of skilled forgery test using the writer-independent approach obtained were 13.09% for LBP, 19.33% for GLCM, 13.18% for HOG and combination of all three resulted in EER of 9.94%. Vaibhav Shah et al. [6] have proposed an architecture for offline signature verification that makes the use of runtime signature instead of scanned images for recognition. Their system uses a set of shape based geometric features and focuses on the distance based parameters such as the continuity of the signature and matching of the curve of the signatures generated by the critical points of the respective signature by analyzing the polynomial equation. Curve fitting and the analyzing of polynomial equations is one of the least explored methods and is very efficient. The authors have used feed forward back propagation neural network to verify the authenticity of the signatures. Based on the inputs, the neural network was trained and according to the target values specified, the corresponding outputs and error values are obtained for the particular parameter under test. The authors implemented their code using 75 samples of genuine signatures and received FAR=2% and FRR=5.26%. M.Nasiri et al. [7] have proposed a system based on fuzzy approach for automatic signature verification. The authors have presented their methodology where they propose to find the points as control points of the boundary of the signature. These boundaries clearly show the structural characteristics of the signature. The authors have extracted four types of local features which are extracted from the control points of the training set of signatures and then these features have been fuzzified for training the Fuzzy Inference System (FIS). Depending on the output of the FIS, the system classifies that the signature is genuine or forged. For each signature, a MAX and MIN value are assigned, if the output of the FIS is between MAX and MIN, thn the signature is classified as genuine and if the output is more than MAX, then it is classified as unskilled forgery and if the value is less than MIN it is classified as skilled forgery. The system proposed by the authors has FRR of 10.3% and FAR of 8.105%. Surabhi Garhawal et al. [8] have presented a brief survey of the recent works on offline signature recognition & verification. The paper explains the significance of offline signature verification systems and explains about the common used terms related t signature verification. Various techniques such as Template Matching, Statistical techniques, Structural techniques, Neural Networks, Fuzzy-logic technique and Evolutionary Computing Techniques have been discussed in the paper and the merits and demerits of all have been provided and compared.
L.B. Mahanta et al. [9] have presented basic concepts of signature verification and have explored the different approaches for verification. The factors such as physical and psychological state of the person, writing surface and writing material that affect the signature have been discussed. Various performance evaluation techniques such as False Acceptance Rate (FAR), False Rejection Rate (FRR), Equal Error Rate (EER) and Error Tradeoff Curve also have been discussed in the paper. The authors have also thrown light upon the various verification approaches such as Statistical approach, Fuzzy based approach, Neural Network based approach , Wavelet
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based approach, Combination of approaches, Clustering technique approach and Support Vector Machine approach. Pradeep Kumar et al. [10] have proposed an offline signature verification system based upon neural network approach. The signatures are captured and presented to the user in an image format and are verified based upon the parameters extracted from the signature using various image processing techniques. Along with the proposed system, the authors discuss about various other approaches to Hand Written Signature Verification (HSV). The model presented uses neural network classifier for verification. Post the pre-processing, the image is used to train the system. The authors chose the Back Propagation ANN technique as it is easiest to implement, while preserving efficiency of the network. The authors used "Grupo de Procesado Digital de Senales" (GDPS) signature database for testing purposes. The database comprised of 2000 signatures, which comprised of 50 sets from different people. When their proposed system was presented with the signatures used in training, the success rate of the system was 100%. When the system was presented signature samples from a database different than the ones used for training, the success rate of 82.66% was obtained. 3. Analysis & Discussion A brief survey of the recent works in the field of offline signature verification and forgery detection has been presented in the paper. By performing this survey it was observed that already a lot of work done in the field, but still there are many challenges in this research area. It was observed that the most successful systems implemented the Artificial Neural Network approach, but the results varied depending upon the choice and the combination of classifiers used and the amount of training provided to the system. It was also observed that the least explored classifier using Curve fitting and the analyzing of polynomial equations showed great success rates. The variation in personality of signatures, because of age, sickness, geographic location and emotional state of the person actuates the problem. Another problem associated with offline signature verification is that, for security reasons, it is not very easy to make a signature dataset of real documents such as banking documents. References [1] Md. Iqbal Quraishi, Arindam Das and Saikat Roy (2013), "A Novel Signature Verification and Authentication System Using Image Transformation and Artificial Neural Netwrok", Narula Institute of Technology, Kolkata. [2] Othman o-khalifa, Md. Khorshed Alam and Aisha Hassan Abdalla (2013), "An Evaluation on Offline Signature Verification using Artificial Neural Network Approach", International Conference on Computing, Electrical and Electronic Engineering (ICCEEE). [3] Rameez Wajid and Atif Bin Mansoor, "Classifier Performance Evaluation For Offline Signature Verification Using Local Binary Patterns", Institute of Avionics & Aeronautics, Air University, Islamabad, Pakistan. [4] Muhammad Imran Malik, Marcus Liwicki and Andreas Dengel, "Evaluation of Local and Global Features for Offline Signature Verification", German Research Center for AI (DFKI GmbH). [5] Juan Hu and Youbin Chen (2013), "Offline Signature Verification Using Real Adaboost Classifier Combination of Pseudo-dynamic Features", 12th International Conference on Document Analysis & Recognition. [6] Vaibhav Shah, Umang Sanghavi, Udit Shah, "Off-line Signature Verification Using Curve Fitting Algorithm with Neural Networks", Dwarkadas J. Sanghvi College of Engineering, Mumbai. [7] M.Nasiri, S.Bayati and F.Safi, "A Fuzzy Approach for the Automatic Off-line Signature Verification Problem Base on Geometric Features", Azad University, Iran. [8] Surabhi Garhawal and Neeraj Shukla (2013), "A Study on Handwritten Signature Verification Approaches", International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), Volume 2, Issue 8, August 2013. [9] L B. Mahanta, Alpana Deka (2013), "A Study on Handwritten Signature", International Journal for Computer Applications (0975-8887), Volume 79 - No. 2, October 2013. [10] Pradeep Kumar, Shekhar Singh, Ashwani Garg and Nishant Prabhat (2013), "Hand Written Signature Recognition & Verification using Neural Network", International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 3, March 2013.