Off-line writer verification utilizing multiple neural networks
Jing Wu · Optical Engineering · 1997
A writer verification system based on multiple neural network classifiers is described, aimed to be easily extendable. Each writer reg- isters with the system by writing a set of discrete Chinese characters. One neural network is constructed for each enrolled character class on a per-person or a per-subgroup basis. The decisions from individual net- work classifiers are combined by voting. The method has been verified to work reliably on our testing database: a verification rate above 96% is achieved on short-term data. © 1997 Society of Photo-Optical Instrumentation En- gineers. (S0091-3286(97)01211-7)