Weighted-function based algorithm for retrieving handwriting trajectory from off-line data
Individuality of handwriting is the reason why it is used as a common base element for detecting character traits of the writer. It is believed that dynamic information improve the accuracy of the analysis, but they are not contained in an offline handwritten text. In order to recover dynamic information, a novel approach for handwriting trajectory recovery is proposed in this paper. The procedure is based on computing the objective function, which depends on parameters such as the angle of movement, path length, air pen tip movements, etc. The analysis is performed in MATLAB program package, using the text samples from IAM-OnDB database. The experimental results indicate that the average effectiveness of the proposed algorithm is above 75%.