Wavelet-based gender detection on off-line handwritten documents using probabilistic finite state automata
作者：
Highlights：
• Prediction of gender from offline images of handwriting using textural information
• Wavelet transform using symbolic dynamic filtering for feature extraction
• Classification using support vector machine and artificial neural networks
• Script-independent approach applied to English, French & Arabic handwritings
• Improved results on the QUWI & MSHD databases once compared to existing methods
摘要
•Prediction of gender from offline images of handwriting using textural information•Wavelet transform using symbolic dynamic filtering for feature extraction•Classification using support vector machine and artificial neural networks•Script-independent approach applied to English, French & Arabic handwritings•Improved results on the QUWI & MSHD databases once compared to existing methods
论文关键词：Off-line handwriting analysis,Gender detection,Texture analysis,Wavelet sub-band,Symbolic dynamics,Probabilistic finite state automata
论文评审过程：Received 14 November 2015, Revised 15 November 2016, Accepted 19 November 2016, Available online 7 December 2016, Version of Record 22 December 2016.
论文官网地址：https://doi.org/10.1016/j.imavis.2016.11.017
