A First Look at Chebyshev-Sobolev Series for Digital Ink
This incremental work addresses symbol recognition in digital ink applications like signature verification and handwriting recognition.
The paper explores using Chebyshev-Sobolev series for digital ink symbol recognition, finding early indications that it may outperform Legendre-Sobolev representations for certain tasks.
Considering digital ink as plane curves provides a valuable framework for various applications, including signature verification, note-taking, and mathematical handwriting recognition. These plane curves can be obtained as parameterized pairs of approximating truncated series (x(s), y(s)) determined by sampled points. Earlier work has found that representing these truncated series (polynomials) in a Legendre or Legendre-Sobolev basis has a number of desirable properties. These include compact data representation, meaningful clustering of like symbols in the vector space of polynomial coefficients, linear separability of classes in this space, and highly efficient calculation of variation between curves. In this work, we take a first step at examining the use of Chebyshev-Sobolev series for symbol recognition. The early indication is that this representation may be superior to Legendre-Sobolev representation for some purposes.