Abstract
AbstractThis paper is a review of works about the use of the log-polar image model for pattern recognition purposes. Particular attention is paid to the rotation- and scale-invariant pattern recognition problem, which is simplified by the log-polar mapping. In spite of this advantage, ordinary translations become a complicated image transform in the log-polar domain. Two approaches addressing the estimation of translation, rotation and scaling are compared. One of them, developed by the authors, takes advantage of the principles of the active vision paradigm.KeywordsActive VisionObject Recognition TaskPattern Recognition TaskHandwritten NumeralCartesian ImageThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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