Open AccessDiagonal Based Feature Extraction and Backpropagation Neural Network in Handwritten Batak Toba Characters Recognition
Author(s) -
Elviawaty Muisa Zamzami,
Septi Hayanti,
Erna Budhiarti Nababan
Publication year - 2021
Publication title -
kinetik
Language(s) - English
Resource type - Journals
eISSN - 2503-2267
pISSN - 2503-2259
DOI - 10.22219/kinetik.v6i2.1212
Subject(s) - backpropagation , pattern recognition (psychology) , feature extraction , computer science , artificial neural network , artificial intelligence , character (mathematics) , preprocessor , feature (linguistics) , character recognition , diagonal , data pre processing , speech recognition , mathematics , image (mathematics) , linguistics , philosophy , geometry
Handwritten character recognition is considered a complex problem since one’s handwritten character has its characteristics. Data used for this research was a photo of handwritten or scanned handwritten. In this research, Backpropagation Neural Network (BPNN) was used to recognize handwritten Batak Toba character, wherein preprocessing stage feature extraction was done using Diagonal Based Feature Extraction (DBFE) to obtain feature value. Furthermore, the feature value will be used as an input to BPNN. The total number of data used was190 data, where 114 data was used for the training process and another 76 data was used for testing. From the testing process carried out, the accuracy obtained was 87,19 %.