Baseline Extraction and Evaluation for Off-line Signature Verification

Bence, Nagy; Bence, Kovari [Kővári, Bence András (informatika), szerző] Automatizálási és Alkalmazott Informatikai Tanszék (BME / VIK)

Angol nyelvű Tudományos Konferenciaközlemény (Könyvrészlet)
    Present-day off-line signature verification methods definitely could and should be improved, considering that not even the best systems can achieve lower error rates than 5 percent. In this paper we present an off-line comparison method for differentiating between genuine and forged signatures based on feature matching, specifically baseline matching. Since a highly modularized framework has already been created, we developed different modules that suited that system, and were able to create a module chain that extracted baseline information from the signatures, and using the knowledge gained from a small learning set could decide whether the signature was forged or genuine. Of course verification based on only one feature can not be perfect, but the results imply that involving additional - more or less - independent features of the signature can decrease the error rate of the system below the barrier of 5 percent.
    Hivatkozás stílusok: IEEEACMAPAChicagoHarvardCSLMásolásNyomtatás
    2021-03-05 05:46