Abstract:

Taking 6763 characters of GB2312 standard as examples, we firstly make the standard templates of regular scripts and collect the handwritings of 45 individuals both in the form of skeleton point sets, from which strokes and components elements are extracted. Then the basic writing features are calculated and assigned to the standard font library templates, thus the basic feature font library of each writer is constructed. Thirdly, we use the SVM and KNN machine learning methods to calculate the structural features of the 45 samples of Chinese characters. The obtained structural features are given to the above basic feature font library of each writer, based on which, the personalized feature library of Chinese characters is constructed. This is called "optimization". Finally, the subjective judgment experiment shows that the optimized fonts have higher acceptability. The proposed method can greatly reduce the difficulty of making personalized font library, relieve the input pressure of the writers, shorten the time of making font library, and save the cost of making font library.

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