Offline handwriting individual recognition system and method based on two-dimensional dynamic features

An offline handwriting individual recognition system based on two-dimensional dynamic features, comprising:

• a data acquisition module, configured to obtain a first handwriting image corresponding to suspicious handwriting, and configured to obtain second handwriting images corresponding to a plurality of sample handwriting;
• a data pre-processing module, connected to the data acquisition module, configured to pre-process the first handwriting image to obtain a first pre-processed image corresponding to the suspicious handwriting, and configured to pre-process each of the second handwriting images to obtain second pre-processed images corresponding to each of the plurality of sample handwritings;
• a skeleton extraction module, connected to the data pre-processing module, configured to perform skeleton extraction on the first pre-processed image to obtain a first skeleton image corresponding to the suspicious handwriting;
• and configured to perform skeleton extraction on each of the second pre-processed images to obtain second skeleton images corresponding to each of the plurality of sample handwritings;
• wherein the first skeleton image and each of the second skeleton images have a line width of a single pixel;
• a stroke order recognition module, connected to the skeleton extraction module, configured to perform handwriting tracking according to the first skeleton image to obtain a first writing trajectory corresponding to the suspicious handwriting, and configured to perform handwriting tracking according to each of the second skeleton images to obtain second writing trajectories corresponding to each of the plurality of sample handwritings;
• a feature extraction module, connected to the data acquisition module and the stroke order recognition module, respectively, configured to perform feature extraction on the corresponding first handwriting image according to the first writing trajectory to obtain a first dynamic feature of each pixel in the first writing trajectory, and configured to perform feature extraction on each of the corresponding second handwriting images according to the each of the second writing trajectories to obtain a second dynamic feature of each pixel in each of the second writing trajectories;
• a first data processing module, connected to the feature extraction module, configured to obtain a correlation coefficient between the suspicious handwriting and each of the plurality of sample handwriting, according to the first dynamic feature corresponding to the suspicious handwriting and the second dynamic feature corresponding to the each of the plurality of sample handwriting;
• and
• a second data processing module, connected to the first data processing module, configured to process, according to a first probability density distribution data and a second probability density distribution data obtained in advance by using statistics and each of the correlation coefficients, to obtain an individual recognition result of the suspicious handwriting.