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Handwritten signature authentication program using a neural network
(2020) Komleva, N. O.; Nevzorov, V. D.
The aim of the work is to improve the quality of handwritten signature recognition by adapting the recognition method to the end user using a neural network. Methods of digital image processing, analytical and computational geometry are used to identify features of signature creation. Development methods are based on java, javafx, c ++ technologies using fann and jni, xml. As a result, a mobile software has been developed that allows recognizing the authorship of a handwritten signature.