Signature recognition

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

A hybrid neural network/rule-based technique for on-line gesture and hand-written character recognition

Abstract: A technique is presented which combines rule-based and neural network pattern recognition methods in an integrated system in order to perform learning and recognition of hand-written characters and gestures in realtime. The GesRec system is introduced which provides a framework for data acquisition, training, recognition, and gesture-to-speech transcription in a Windows environment. A recognition accuracy of 92.5% was obtained for the hybrid system, compared to 89.6% for the neural network only and 82.7% for rules only. Training and recognition times are given for an able-bodied and a disabled user.

Recognising face features and faces

Abstract: In order to develop a successful face-recognition system, it is necessary to remove instance-specific detail from an incoming image, before attempting to match against previously stored codes. Very recently hybrid methods have emerged, which make use of known feature locations either implicitly, or explicitly to provide much better input to a recognition component which has many of the characteristics of a net based method. The author describes one such hybrid scheme, presenting details of a working system for locating face features; and a coding scheme, based on accurate feature location, which is useful for recognition. The author describes some applications. An advantage of feature recognition over net-based methods is the detailed understanding available at an intermediate stage; this can sometimes be valuable in its own right.

Method and system for signature recognition biometrics on a fob

Abstract: The present invention discloses a system and methods for biometric security using signature recognition biometrics in a transponder-reader system. The biometric security system also includes a signature scan sensor that detects biometric samples and a device for verifying biometric samples. In one embodiment, the biometric security system includes a transponder configured with a signature scan sensor. In another embodiment, the system includes a reader configured with a signature scan sensor. In yet another embodiment, the present invention discloses methods for proffering and processing signature samples to facilitate authorization of transactions.

Impact of time variability in off-line writer identification and verification

Abstract: One of the biggest challenges in person recognition using biometric systems is the variability in the acquired data. In this paper, we evaluate the effects of an increasing time lapse between reference and test biometric data consisting of static images of handwritten signatures and texts. We use for our experiments two recognition approaches exploiting information at the global and local levels, and the BiosecurlD database, containing 3,724 signature images and 532 texts of 133 individuals acquired in four acquisition sessions distributed along a 4 months time span. We report results of the recognition systems working both in verification (one-to-one) and identification (one-to-many) mode. The results show the extent of the impact that the time separation between samples under comparison has on the recognition rates, being the local approach more robust to the time lapse than the global one. We also observe in our experiments that recognition based on handwritten texts provides higher accuracy than recognition based on signatures.