Experimental evaluation of an on-line scribble recognizer

  title={Experimental evaluation of an on-line scribble recognizer},
  author={Manuel J. Fonseca and Joaquim A. Jorge},
  journal={Pattern Recognition Letters},
We present a fast, simple and compact approach to recognize scribbles (multi-stroke geometric shapes) drawn with a stylus on a digitizing tablet. Regardless of size, rotation and number of strokes, our method identifies the most common shapes used in drawings, allowing for dashed, continuous or overlapping strokes. Our method combines temporal adjacency, Fuzzy Logic and geometric features to classify scribbles with measured recognition rates over 97%. 


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