Signature recognition

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

An efficient approach for dynamic signature recognition

Abstract: Online signature recognition is an accepted biometric technique, because it is less expensive than other biometric techniques. In this paper, an efficient two-stage online signature recognition approach is presented. This approach depends on the initial analyses of global features using Euclidean distance to quickly discard outlier signatures; then followed by local features analysis using an enhanced DTW algorithm. An emphasis was created to extract stroke-associated features for global recognition phase as well as for signal pre-processing prior to local recognition. Stroke-related features used in the proposed system contribute well in enhancing the run-time performance by quick discriminating genuine and forgery signatures. Experiments are run out on MCYT-100 benchmark database. The proposed system is tested with 100 users - including 25 skilled forgery signatures and 25 genuine signatures per each user. The worst FAR recorded value is less than 4%, FRR is less than 20% and EER is less than 5%.

A Study on Design and Implementation of Embedded System for speech Recognition Process

Abstract: This study attempted to develop a speech recognition module applied to a wheelchair for the physically handicapped. In the proposed speech recognition module, TMS320C32 was used as a main processor and Mel-Cepstrum 12 Order was applied to the pro-processor step to increase the recognition rate in a noisy environment. DTW (Dynamic Time Warping) was used and proven to be excellent output for the speaker-dependent recognition part. In order to utilize this algorithm more effectively, the reference data was compressed to 1/12 using vector quantization so as to decrease memory. In this paper, the necessary diverse technology (End-point detection, DMA processing, etc.) was managed so as to utilize the speech recognition system in real time.

On some optimalization of signature recognition

Abstract: Signature recognition is one of the important problems nowadays. In paper we present known method of pattern (curves) recognition, i.e. algorithm IPAN99 and researches over its optimization; there are many control parameters which influence on recognition results. We present some quasi-optimal set of control parameter. Our next aim is to automatically find proper parameters. Thus some optimum seeking method for unimodale and multimodale function is proposed.

A comparative study on signature recognition

Abstract: Contour and shape are the major point for signature recognition. There are a few approaches that have been used for shape detection, particularly to signature recognition. Combination methods of geometric features such as ratio, contour, shape or moment like Zernike moment, Moment Invariants (Hu) usually have been used to identify the signature. One method never been used for signature recognition, Polar Fourier Transform. In this paper, a comparative study is conducted to compare three methods, Moment Invariants (Hu), Zernike Moment, and Polar Fourier Transform (PFT). Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used to classify 20 person data set in each of which consists of 15 genuine signatures and 15 forgery signatures. The result shows that the methods using PFT and SVM achieves accuracy of 86.67%. Whilst the computational time of SVM is faster than MLP. The SVM method had an average value of 0.012 seconds for computational time.

Hybrid Authentication System A Survey

Abstract: This work offers simple but practical method for signature recognition, Discrete Wavelet Transform. Research shows that proposed work have developed a near real time computer system that can locate and track a subject head and then recognize the person by comparing authentication of known individual.