Rotation invariant pattern recognition using Zernike moments

A method for recognizing an object in a binary image regardless of its orientation is discussed. The technique is also insensitive to slight deviation in shape and structure from a reference. The rotation-invariant features are the magnitudes of the Zernike moments of the image. Unlike classical moments, the Zernike moments are a mapping of the image onto a set of orthogonal basis functions, which gives them many useful properties. A novel synthesis-based approach for selection of these features is presented. Using this procedure, the discrimination power of features is evaluated by examining dissimilarities among images synthesized from them for different patterns. The method, applied to recognition of all English characters, yielded 95% accuracy