Identification of Speed and Unique Letter of Handwriting Using Wavelet and Neural Networks - Esmeralda Contessa Djamal (IAES Indonesia Section, 2015)
Handwriting stroke reflects the personality and emotional condition. Graphology is scientific method to evaluation personality through handwriting. There are many features in graphology to identify personality. Several previous researches used page margins, spacing, baseline, vertical zone, font size, and the type of unique letter t. Other research also identify the personality of signatures. This research uses feature writing speed and the type of letters a, d, i m, and t to identify personalities using structural analysis and artificial neural networks. To improve accuracy, image writing extracted using wavelet transform. The system is built with the approach of the structure and symbol has been implemented in software. The results show a unique type of letter recognition by 74%, and the speed feature by 60% recognition. Variations training data greatly affect recognition results.