Scale-invariant pattern recognition using a combined Mellin radial harmonic function and the bidimensional empirical mode decomposition.

A novel scale and shift invariant pattern recognition method is proposed to improve the discrimination capability and noise robustness by combining the bidimensional empirical mode decomposition with the Mellin radial harmonic decomposition. The flatness of its peak intensity response versus scale change is improved. This property is important, since we can detect a large range of scaled patterns (from 0.2 to 1) using a global threshold. Within this range, the correlation peak intensity is relatively uniform with a variance below 20%. This proposed filter has been tested experimentally to confirm the result from numerical simulation for cases both with and without input white noise.