Signature recognition

About: Signature recognition is a research topic. Over the lifetime, 2138 publications have been published within this topic receiving 37605 citations.

Pattern recognition by embedded reduced number of angles fingerprint algorithm in biometric machines augments security

Abstract: In this paper, a biometric machine with embedded RNA-FINNT reduced number of angles fingerprint hash algorithm with specifications is proposed. The essential objective is to propose a methodology for enhancement of security at all platforms where biometric identity authentication is implemented. For this purpose, existing algorithms and techniques are first introduced with their proposed methodology, drawbacks and results. Then RNA-FINNT implementation is discussed and compared with the existing algorithms and techniques, and the advantages and results of it are derived. Illustrative experiment and results are analysed to prove the augmentation of security in the biometric machines. In particular, the proposed method enhances the security and privacy for identity authentication through biometric machines.

On-line signature verification based on modified dynamic time warping and wavelet sub-band coding

Abstract: This paper presents an on-line signature biometric system based on a modified Dynamic Time Warping (DTW) algorithm applied to the signature wavelet coefficients. The modification on DTW relies on the use of direct matching points information (DMP) to dynamically adapt the similarity measure during the matching process, which is shown to increase the verification success rate. The wavelet analysis is done using a sub-band coding algorithm at global and local level. The use of wavelet coefficients showed a considerable reduction in processing time and an improvement in the equal error recognition rate (EER). The system was tested using a locally constructed database. A comparison of the ROC curves obtained in each case is presented.

Automatic signature verification system

Abstract: In this thesis, we explore dynamic signature verification systems. Unlike other signature models, we use genuine signatures in this project as they are more appropriate in real world applications. Signature verification systems are typical examples of biometric devices that use physical and behavioral characteristics to verify that a person really is who he or she claims to be. Other popular biometric examples include fingerprint scanners and hand geometry devices. Hand written signatures have been used for some time to endorse financial transactions and legal contracts although little or no verification of signatures is done. This sets it apart from the other biometrics as it is well accepted method of authentication. Until more recently, only hidden Markov models were used for model construction. Ongoing research on signature verification has revealed that more accurate results can be achieved by combining results of multiple models. We also proposed to use combinations of multiple single variate models instead of single multi variate models which are currently being adapted by many systems. Apart from these, the proposed system is an attractive way for making financial transactions more secure and authenticate electronic documents as it can be easily integrated into existing transaction procedures and electronic communications

Feature feedback-based system for recognition of handwritten Chinese characters

Abstract: Due to the difficulty of conforming to human recognition process with traditional open loop recognition system,a simulated intelligent recognition system with feedback structure was constructedChoosing the best initial recognition method based on the multimodal and qualitative recognition result,the system extracted general characters recognition error to judge the credibility and feedback correction after the initial recognitionThree kinds of general characters recognition error were designed according to the feedback resultThe credibility evaluation index system and feedback correction decision-making mechanism of the recognition result were established by qualitative and quantitative analysis of three kinds of general characters recognition errorAnd the analytical method of the recognition error was givenThe experimental results prove that the presented method is effective

Gait Recognition System for Improved Human Identification using

Abstract: Recognition of any individual is a task to identify people. Human identification using Gait is method to identify an individual by the way he walk or manner of moving on foot. Gait recognition is a type of biometric recognition and related to the behavioural characteristics of biometric recognition. Gait recognition is one kind of biometric technology that can be used to monitor people without their cooperation. Controlled environments such as banks, military installations and even airports need to be able to quickly detect threats and provide differing levels of access to different user groups. Gait shows a particular way or manner of moving on foot and gait recognition is the process of identifying an individual by the manner in which they walk. Gait is less unobtrusive biometric, which offers the possibility to identify people at a distance, without any interaction or co-operation from the subject; this is the property which makes it so attractive. In this thesis, firstly binary silhouette of a walking person is detected from each frame. Secondly, feature from each frame is extracted using image processing operation. Here center of mass, step size length, and cycle length are talking as key feature. At last NN and ENN technique is used for training and testing purpose. Here all experiments are done on gait database and input video.