Handwriting movement analysis by synthesis of synergic primitives
Guoli Wang · Caai Transactions on Intelligent Systems · 2010
A novel methodology of handwriting analysis was explored in relation to the biological motor control hypothesis and the data analysis by a synthetic approach.In particular,the main concern was the issue of handwriting data analysis with movement primitives,in which the analysis by a synthetic approach was presented to build a data understanding paradigm that respects the synergic hypothesis of the biological motor control.The proposed synthetic analysis approach was comprised of two alternately iterative optimization algorithms;the non-negative matrix factorization paradigm was applied for primitive decompositions while the correlative maximization principle was employed for estimating activation time of synergic primitive.The experimental studies for stroke segmentation obtained by the synthesis of synergic primitives validate the proposed method by showing that the superposed connection mode of neighboring strokes can be recognized from handwriting data.