Vector-to-Image Transformation of Character Patterns for On-line and Off-line Recognition
Ondrej Velek, Masaki Nakagawa, Cheng‐Lin Liu · International Journal of Computer Processing Of Languages · 2002
This paper proposes a method to generate realistic character images from on-line patterns. From the pen trajectory of an on-line pattern, the proposed method generates images of various stroke shapes using four painting modes: constant line mode, proportional mode and two calligraphic modes. Particularly, the calligraphic modes combine the pen trajectory with real stroke-shape images so that the generated images resemble the characters produced with brush pen. In the calligraphic painting mode based on primitive stroke identification (PSI), the strokes of on-line patterns are classified into different classes and each class of strokes is painted with the corresponding stroke shape template; while in the calligraphic painting mode based on stroke component classification (SCC), each stroke is decomposed into ending, bending and connecting parts, and each part is painted with a stroke shape template. Decomposing strokes into parts is helpful to deal with connected strokes in cursive writing. Our method of image transformation serves two purposes: supplying image samples for off-line recognition, and application of off-line recognition methods to on-line recognition. The experimental results show that our methods are well suited for both purposes. We show that calligraphic painting mode is appropriate for off-line recognition while constant line mode and proportional mode are appropriate for on-line recognition.