| Signature, as one of the behavioral characteristics of human beings, is one of the traditional methods used to represent personal identity. Signature verification has become a well-known identity identification technology with its characteristics of uniqueness, dignity, and convenience. On-line handwriting signature verification is a new automatic personal identification technique through data acquisition and signature verification done by computer.An embedded on-line signature data acquisition system, whose core is the single chip microcomputer AT89S52, is designed. Signature signal is sensed through a 4-wire resistance touch panel, and signature coordinates and pressure information are collected through touch panel controller ADS7846 during the period of signature. A USB interface, whose control chip is PDIUSBD12, is designed for communication between the system and personal computer.An on-line signature database is constructed. Almost 5000 signatures from 40 subjects are collected in the well-organized on-line signature acquisition activities on a large scale. The genuine signature database is constituted totally by genuine signatures, while random forgery signatures, skilled forgery signatures, and timing forgery signatures constitute the forgery signature database.A real-time on-line signature verification system is accomplished, and a two-level verification mechanism is proposed.The first stage verification adopts parameter feature method, which is based on the matching of signature energy features. An on-line handwriting signature verification algorithm is proposed based on wavelet theory. First, by means of Daubechies wavelet decomposition of signature waveform, and after reconstruction of part signal, the energies of sharp trajectory change points in the signature waveform are extracted, and the M most dominant energies are chosen as feature vector. A new algorithm for evaluating the similarity between the testing signature and the reference signature is put forward, which is based on the signature energy feature. The comparison of energy features between the testing signature and the reference signature is made through the method that directly arranges in descending order the signature energies and the method that is based on DTW (Dynamic Time Warping). The presented algorithm based on energy feature is capable of eliminating quickly random forgeries for automatic signature verification.The second stage verification adopts function feature method, which is based on the matching of signature curve segments. Owing to the randomness of on-line signatures, and it is very difficult for functions to express the signature waveform. After the establishment of the similarity comparison criteria between the two signatures, the paper proposes the matching model of signature verification. As a result, matching problem can be converted into function optimal problem. A general optimal method is difficult to solve the kind of signature problem, but EC (Evolutionary Computation) is easy to do so for its comparison of fitness is only required. Based on EC, an algorithm of optimal curve segment matching between the testing signature and the reference signature is proposed. In order to solve the problem of time nonlinearity during the period of signature, the dynamic segmentation matching algorithm of the signature waveforms is proposed. As the new solutions generated by EC are out-of-order, and the balance problems between the search effect and efficiency exist in the algorithm design, the neighborhood search strategy based on the similarity and the search strategy based on the classification of the individuals by the fitness are adopted. In the meanwhile, filial-populations are processed through the acceleration operation in order to get better solution sets and to improve the search efficiency. In this stage, the main purpose is to eliminate the skilled forgery signatures and timing forgery signatures, and to improve the accuracy of the verification.
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