3D object recognition through processing of 2D holograms.

Correlation of two-dimensional digitally recorded holograms is introduced as a novel approach for object recognition without the need for quantitative assessment of the retrieved complex field, based on the fact that a hologram contains the three-dimensional information of the object. Actual objects with different three-dimensional features such as depth and surface roughness are assessed through processing of the correlation of their two-dimensional holograms. Correlation peak values are extracted as a metric to evaluate correlation of three-dimensional objects. The effect of hologram windowing size on correlation of three-dimensional objects is investigated, and improvements in computation time and dynamic range are assessed. Critical figures of merit used for assessment of correlation of images are applied to the correlation of holograms for object recognition.

[1]  Koichi Fujiwara,et al.  Development of correlation-based pattern recognition algorithm and adaptive soft-sensor design , 2012 .

[2]  J Khoury,et al.  Photorefractive two-beam coupling joint transform correlator: modeling and performance evaluation. , 2016, Applied optics.

[3]  Partha P. Banerjee,et al.  Effect of Hologram Size on 3D Reconstruction using Multi-wavelength Digital Holography , 2019, Digital Holography and Three-Dimensional Imaging 2019.

[4]  Mohammad A. Karim,et al.  Multiple target detection using a modified fringe-adjusted joint transform correlator , 1994 .

[5]  T Kim,et al.  Three-dimensional matching by use of phase-only holographic information and the Wigner distribution. , 2000, Journal of the Optical Society of America. A, Optics, image science, and vision.

[6]  Bahram Javidi,et al.  Reduction of speckle in digital holography by discrete Fourier filtering. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.

[7]  A Mahalanobis,et al.  Distance-classifier correlation filters for multiclass target recognition. , 1996, Applied optics.

[8]  P P Banerjee,et al.  Holographic volume displacement calculations via multiwavelength digital holography. , 2014, Applied optics.

[9]  D. Casasent,et al.  Correlation synthetic discriminant functions. , 1986, Applied optics.

[10]  Toshimitsu Asakura,et al.  Effect of surface roughness on the statistical distribution of image speckle intensity , 1974 .

[11]  Ujitha Abeywickrema,et al.  High-resolution topograms of fingerprints using multiwavelength digital holography , 2017 .

[12]  L P Yaroslavsky.  Optical correlators with (-k)th-law nonlinearity: optimal and suboptimal solutions. , 1995, Applied optics.