Abstract
This paper introduces a new set of orthogonal moment Functions-franklin Moments (FMs). The kernel functions of FMs is Franklin set, which is a class of complete orthogonal spline function set of degree 1. The implementation of FMs does not involve any numerical approximation and has a rather low computation complexity, since the basis set has the advantages of lower order. These properties make FMs superior to the conventional orthogonal moments such as Legendre moments and Zernike moments, in terms of the image reconstruction. Our simulation results also show that FMs have a better feature representation capability.
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