Open AccessDirectional Zernike moments for rotation‐free recognition of online sketched symbols
Author(s) -
Zhang Yougen,
Wu Lingda,
Song Hanchen
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2013.1680
Subject(s) - zernike polynomials , rotation (mathematics) , artificial intelligence , computer science , pattern recognition (psychology) , optics , physics , computer vision , algorithm , mathematics , wavefront
A new description method is proposed for sketched symbol recognition. It incorporates local direction information into the Zernike moments which represent only the spatial distribution of sample points. A symbol is decomposed into several component patterns according to the local direction of sample points before Zernike moments computation. The resulting descriptor inherits from the traditional Zernike moments descriptor the invariability to stroke number, stroke order and symbol rotation. Moreover, the fusion of both types of data makes it more informative and discriminative, resulting in better performances in both rotation‐invariant classification and rotation angle estimation.