Invariant optical-pattern recognition based on a contour bank

Invariant pattern recognition based on centroids

A new method for pattern recognition that is invariant under changes of position, orientation, intensity, and scale is presented. The centroids of objects provide unique points that are related to the energy distribution. For obtaining more such unique points a conformal transform can be used to rearrange the energy distribution of the object. By means of the conformal transform many different centroids can be produced from the same object. A useful pattern-recognition and object-registration method that yields a position-, rotation-, intensity-, and scale-invariant feature vector based on these centroids can be created.

Projection-invariant pattern recognition with a phase-only logarithmic-harmonic-derived filter

A phase-only filter based on logarithmic harmonics for projection-invariant pattern recognition is presented. This logarithmic-harmonic-derived filter is directly calculated in the Fourier plane. With respect to normal logarithmic-harmonic filters it provides a smaller variation of the correlation intensity with the projection factor of the target. Computer and optical experiments are presented.

Rotation- and scale-invariant feature extraction by a diffractive optical inner-product transform

A diffractive optical element that is capable of extracting rotation- and scale-invariant features from input images is presented. The diffractive optical element performs an inner product between the input image and a set of basis functions. This set of basis functions is derived from that used in the Fourier-Mellin transform. Simulated results from scaled and rotated versions of two input images are presented.