The paper proposes a simple, low-cost signature verification approach and software that can be employed as one of the components of a more sophisticated personal identification system. The identification is based on the use of local binary pattern features of a signature image. The Support Vector Machine (SVM) model is chosen to classify the authentic signatures from their imitations.