The Interpersonal and Intrapersonal Variability Influences on Off-Line Signature Verification Using HMM
نویسندگان
چکیده
The off-line signature verification rests on the hypothesis that each writer has similarity among signature samples, with small distortion and scale variability. This kind of distortion represents the intrapersonal variability [3]. This paper reports the interpersonal and intrapersonal variability influences in a software approach based on Hidden Markov Model (HMM) classifier [1,5,7]. The experiments have shown the error rates variability considering different forgery types, random, simples and skilled forgeries. The mathematical approach and the resulting software also report considerations in a real application problem.
منابع مشابه
A comparison of SVM and HMM classifiers in the off-line signature verification
The SVM is a new classification technique in the field of statistical learning theory which has been applied with success in pattern recognition applications like face and speaker recognition, while the HMM has been found to be a powerful statistical technique which is applied to handwriting recognition and signature verification. This paper reports on a comparison of the two classifiers in off...
متن کاملSupport vector machines versus multi-layer perceptrons for efficient off-line signature recognition
– The problem of automatic signature recognition has received little attention in comparison with the problem of signature verification despite its potential applications for accessing security-sensitive facilities and for processing certain legal and historical documents. This paper presents an efficient off-line human signature recognition system based on Support Vector Machines (SVM) and com...
متن کاملApplying dynamic methods in off-line signature recognition
In this paper we present the work developed on off-line signature verification using Hidden Markov Models (HMM). HMM is a well-known technique used by other biometric features, for instance, in speaker recognition and dynamic or on-line signature verification. Our goal here is to extend Left-to-Right (LR)-HMM to the field of static or off-line signature processing using results provided by imag...
متن کاملA systematic comparison between on-line and off-line methods for signature verification with hidden Markov models
This paper presents an extensive investigation of various HMM-based techniques for signature verification. Different feature extraction methods and HMM topologies are compared in order to obtain an optimized high performance signature verification system. Furthermore, this paper may be the first systematic comparison of online and off-line methods for signature verification using exactly the sa...
متن کاملAn Off-Line Signature Verification System using Hidden Markov Model and Cross-Validation
This work has as main objective to present an off-line signature verification system. It is basically divided into three parts. The first one demonstrates a pre-processing process, a segmentation process and a feature extraction process, in which the main aim is to obtain the maximum performance quality of the process of verification of random falsifications, in the false acceptance and false r...
متن کامل