Slant in handwriting recognition

In this demo, the geometrical 'shear' transform on XY-coordinates representing handwritten words is shown. Since slant is a free parameter to the writer (within a given range) it must be normalized before extracting the features from sampled handwriting. Here, you may see the effects of shearing on the handwritten trace, by interactively adjusting the slant angle. Within an automatic recognition system, the slant of the input sample must be estimated automatically. Subsequently, the shear transform is applied to obtain a normalized slant.

  1. Calculate the means for x and y, i.e., Xm and Ym.
  2. Subtract Xm from x, subtract Ym from y
  3. Given an estimated slant Phi, and a required slant Phi_norm, apply the shear transform to obtain x' and y':

  4. Obtain x'+Xm and y'+Ym to translate back to the same center of gravity as the input.

After this transform, the extracted features will be more stable, provided that the original slant estimate is reliable (Teulings et al., 1990). In short words or isolated letters, it is often difficult to obtain reliable estimates due to the small number of usable points. From a human reading experiment, it was determined that the angle of the trace at a point somewhere in the middle of down strokes coincides with the slant which human readers would indicate (Maarse & Thomassen (1983). Produced and perceived writing slant: difference between up and down strokes, Acta Psychologica, 54, 131-147.) A good choice would be to take the point of maximal velocity (minimum curvature) in down strokes, as is done in our handwriting recognizer. The histogram of slant angles per word is analyzed and outliers are removed to get a good estimate.

Please refer to our Publications when using anything from the shown material.

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An interactive demo of (un)slanting in handwriting recognition.

Source code

Notes:

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Up to the Java-based Handwriting Demos page

Up to NICI's on-line handwriting recognizer description

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Other interesting material:

o Handwriting Recognition and Document Analysis Conferences

o Pen & Mobile Computing

o NICI Handwriting Recognition Group home page

o UNIPEN tools

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Copyright Lambert Schomaker (April 1, 1996)

since 1/Mar/1996