According to the American National Science and Technology Council (NSTC), the first signature recognition system was developed in 1965. Then the research continued in 1970 focusing on the potential of geometric characteristic of a signature rather than dynamic characteristic. Nowadays, signature is a commonly used identification procedure. Everyone would be required having a signature for autho...

In this work a new offline signature recognition system based on Radon Transform, Fractal Dimension (FD) and Support Vector Machine (SVM) is presented. In the first step, projections of original signatures along four specified directions have been performed using radon transform. Then, FDs of four obtained vectors are calculated to construct a feature vector for each signature. These vectors ar...

Face and signature are still two most dominant authentication modes in banking, legal documents, or personnel records in spite availability of more robust biometric modes. Hence, it is imperative to develop low-cost and reliable automated face recognition and signature verification system. Therefore, this paper presents our work in development of a two-in-one portable low-cost dsPIC30F3013 digi...

Signature is one of the important method of individual authentication and identification. Signatures. A variety of techniques have been proposed for signature identification in the past. Handwritten signatures are one of the most and effective method of authenticating an individual’s identity. Lot of research is going on for signature recognition. In this paper we have used image processing tec...

This paper describes a new visual representation of motion that is used to learn and classify body language what we call “body signatures” of people while they are talking. We applied this technique to several hours of internet videos and television broadcasts that include US politicians and leaders from Germany, France, Iran, Russia, Pakistan, and India, and public figures such as the Pope, as...

Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capability to reliably distinguish between an authorized person and an imposter. Signature verification systems can be categorized as offline (static) and online (dynamic). This paper presents a neural network based recognition of offline handwritten signatures system t...

In our previous research work, an individual recognition system with writing pressure employing neurotemplate of multiplayer feedforward network with sigmoid function has been developed. Although this system was effective on recognition for known registrant, its rejection capability for counterfeit signature was not good enough for commercial application. In this paper, a new activation functio...

Motion trajectory can be an informative and descriptive clue that is suitable for the characterization of motion. Studying motion trajectory for effective motion description and recognition is important in many applications. For instance, motion trajectory can play an important role in the representation, recognition and learning of most long-term human or robot actions, behaviors and activitie...

The most commonly used protection mechanisms today are based on either what a person possesses (e.g. an ID card) or what the person remembers (like passwords and PIN numbers). However, there is always a risk of passwords being cracked by unauthenticated users and ID cards being stolen, in addition to shortcomings like forgotten passwords and lost ID cards (Huang & Yan, 1997). To avoid such inco...

This paper proposed feature extraction method based on centre of gravity for offline signature. Similar to other biometric measures, signatures have inherent variability and so pose a difficult recognition problem. Signature probably is one of the oldest biometric recognition methods, with high legal acceptance Signature has been a distinguishing feature for person identification through ages. ...