INVARIANT PATTERN-RECOGNITION USING ANGULAR SIGNATURE FUNCTIONS

A new concept for invariant pattern recognition is presented that uses object contour information. First, an angular signature of the object contour is obtained by a nonlinear operation applied to two-dimension al directional convolutions with a long, narrow kernel. The angular si gnature function is normalized by either its area or its energy to ach ieve quasi-invariance to scale. The resulting signature is then compar ed with template signatures for the invariant recognition for which an angular similarity measure is obtained from a one-dimensional correla tion between the two signatures. Numerical experiments demonstrate tha t the method discussed exhibits invariance to shift and angular orient ation and quasi-invariance to scale.