Distortion invariant pattern recognition with phase filters.

Pattern recognition using reduced information content filters.

Pattern recognition by optical spatial filtering procedures is discussed using general considerations with the objective of reducing the information content in the spatial filter. The achievement of this objective is very useful toward the wide application of spatial light modulators and also for facilitating distortion invariant recognition. The proposed novel approach is demonstrated by an ex...

Distortion invariant 3D object recognition using digital holography

We present a method to recognize three-dimensional objects from phase-shift digital holograms. The holograms are used to reconstruct various views of the objects. These views are combined to create nonlinear composite filters in order to achieve distortion invariance. We present experiments to illustrate the recognition of a 3D object in the presence of outof-plane rotation and longitudinal shi...

Fully Scale and In-plane Invariant Synthetic Discriminant Function Bandpass Difference of Gaussian Composite Filter for Object Recognition and Detection in Still Images

A difficult pattern recognition problem is to recognize objects despite distortions in position, orientation and scale in cluttered backgrounds. A system capable of detecting target objects despite any kind of geometrical distortion has many potential applications since it will be able to detect target objects when the orientation and position of the target or camera is unknown. In this work we...

Scale invariant pattern recognition with logarithmic radial harmonic filters.

A generalized approach leads to spatial filters that accept changes of scale by a factor of 4. The procedure employs phase filters with reduced tolerance requirements and achieves high discrimination capability and efficient light throughput. Computer simulations and laboratory experiments show the advantages of this novel approach.

Distortion-invariant Kernel Correlation Filters for General Object Recognition