Open AccessSignature recognition using neural network probabilistic
Author(s) -
Heri Nurdiyanto,
Hermanto Hermanto
Publication year - 2016
Publication title -
ijain (international journal of advances in intelligent informatics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.183
H-Index - 9
eISSN - 2548-3161
pISSN - 2442-6571
DOI - 10.26555/ijain.v2i1.53
Subject(s) - computer science , pattern recognition (psychology) , artificial intelligence , preprocessor , probabilistic neural network , probabilistic logic , entropy (arrow of time) , artificial neural network , signature (topology) , data mining , data pre processing , feature extraction , identification (biology) , time delay neural network , mathematics , physics , geometry , botany , quantum mechanics , biology
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%.