Title of article :
Signature recognition using neural network probabilistic
Author/Authors :
Nurdiyanto , Heri Department of Informatics Engineering - STMIK Dharma Wacana, Indonesia , Hermanto , Department of Informatics Engineering - STMIK Dharma Wacana, Indonesia
Abstract :
The signature of each person is different and has unique characteristics. Thus, this paper discusses the development of a personal identification system based on it is unique digital signature. The process of preprocessing used gray scale method, while Shannon Entropy and Probabilistic Neural Network are used respectively for feature extraction and identification. This study uses five signature types with five signatures in every type. While the test results compared to actual data compared to real data, the proposed system performance was only 40%.
Keywords :
identification of signatures , entropy , probabilistic neural network
Journal title :
International Journal of Advances in Intelligent Informatics