Segmentation/Recognition of Hand-Written Numeral Characters
Khalid Sherdil · Open Scholarship Institutional Repository (Washington University in St. Louis) · 1993
This thesis describes a number of techniques for segmenting non-cursive handwritten digits into individual characters. It strongly emphasizes on a recognition-segmentation algorithm, which uses the linear regression method to recognize those strokes which consist of one or more straight-lined parts. A new method of sampling the pen data according to the pen speed, hence giving a more uniform points concentratino distribution, is also introduced. It is shown how several of our segmenting techniques, such as relative stroke lengths, relative stroke positions, order of stroke entry, stroke direction, stroke intersection, etc. can be combined to yield success results of about 95%.