PDA Collected Signatures

The database contains signatures of 15 people and 3 forgers collected using a Windows Mobile PDA device [285 signatures - SVC2004 format]

Determining valuable ranges of handwritten signature using fuzzy approach and window method

The paper proposes possible improvements in signature recognition approach based on window method. The analysis focuses on a stage of window preprocessing using fuzzy sets in order to choose significant ranges of each signature. Proposed extension allows the solution to improve in two areas. First of all minimizing a number of processed windows significantly reduces computation time. Secondly, filtered signatures with valuable information about significant ranges allow the system to recognize signatures of a poor or good quality. Developed method of signature quality assessment can be used in any signature recognition system, regardless of used method of analysis. Merging the information about signature quality and choosing only important signature ranges should also improve the overall detection results, however, more examinations are needed to confirm this statement

The method of signature recognition based on least squares contour alignment and windows technique

This paper presents a new method of recognizing handwritten signatures. Signature was treated as a collection of features of specific values. As features the values of x, y coordinates of signature points have been used. The method discussed in the paper is a modification of the method based on least squares contour alignment. This modification consists of dividing signatures into windows of the preset size and measuring the value of similarity between the windows according to their position in the signature. The effectiveness of the method was verified in practice. During the study, the influence of the parameters of the method on the obtained results was determined

On some optimalization of signature recognition

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

Using hidden Markov models in signature recognition process

This paper presents a method of recognition of handwritten signatures with the use of Hidden Markov Models (HMM). The method in question consists in describing each signature with a sequence of symbols. Sequences of symbols were generated on the basis of an analysis of local extremes determined on diagrams of dynamic features of signatures. For this purpose, the method proposed by G.K. Gupta and R.C. Joyce has been modified. The determined sequences were then used as input data for the HMM method. The studies were conducted with the use of the SVC2004 database. The results are competitive in relation to other methods known from the literature

The method for determining the characteristic points of signatures based on IPAN99 algorithm

The paper puts forward a new method of determination of signatures' characteristic points. The method is based on seeking points of the highest curvature using the IPAN99 algorithm. The way of IPAN99 algorithm parameters' automatic selection for a particular signature has been fully described. Moreover, the way of determination of additional characteristic points, important for a signatures analysis, has been shown. The presented results of carried out experiments confirm that the proposed method is useful for signature recognition and verification

New methods to determine similarity of signatures based on local extremes

Authentication based on handwritten signature is one of the most accepted authentication systems based on biometry. In this paper a method for the automatic verification of on-line handwritten signatures using three similarity measures is described. The proposed approach, is based on extreme values and dynamic features of the signature. In investigations proposed coefficients together with the factor [R2] were connected and new signature recognition quality has been achieved

New method for finding a reference point in fingerprint images with the use of the IPAN99 algorithm

This study presents a new method for finding a reference point in fingerprint images. The proposed method is based on the IPAN99 algorithm, which detects high curvature points on a contour of a graphical object. This algorithm was adjusted in the study to detect high curvature points on friction ridges. It allows locating a reference point on a fingerprint image. Since the IPAN99 algorithm requires that the thickness of an analysed contour should be of one pixel, each fingerprint image was adequately prepared before submitting to the analysis with the IPAN99 algorithm. Evaluation of the efficiency of the method consisted in comparing the distances between coordinates of reference points determined with the use of the proposed method and indicated by an expert. The developed method was compared with other algorithms used for determining a reference point