On-line text/drawings segmentation of handwritten patterns

A simple and fast segmentation of text and line drawings which exploits the characteristics of online handwritten patterns is presented. Many attempts have been made on text/figure segmentation in offline research, but none in online. In online environment, mode selection is easily employed to input characters and drawings commongly. But it disturbs the user´s thought. The authors propose online but delayed processing of handwritten patterns after they are written. Because the input patterns consists of characters and line drawings, there is a need to discriminate input patterns into characters and line drawings. An analysis of 17 handwritten patterns shows that the logarithmic distribution of character stroke length and that of the length of the longer side of rectangles circumscribing character strokes have similarity to the normal distribution. This finding, the contact frequency of character strokes and drawing strokes, and stroke input order have been used to perform the segmentation. In the testing of 18 patterns, 88% of all strokes were correctly judged