Abstract

The Talbot effect is utilized to correct an alignment problem related to a neural network used for image recognition, which required the alignment of a spatial light modulator (SLM) with the input module. A mathematical model which employs the Fresnel diffraction theory is presented to describe the method. The calculation of the diffracted amplitude describes the wavefront sphericity and the original object transmittance function in order to qualify the lateral shift of the Talbot image. Another explanation is set forth in terms of plane-wave illumination in the neural network. Using a Fourier series and by describing planes where all the harmonics are in phase, the reconstruction of Talbot images is explained. The alignment is effective when the lenslet array is aligned on the even Talbot images of the SLM pixels and the incident wave is a plane wave. The alignment is evaluated in terms of source and periodicity errors, tilt of the incident plane waves, and finite object dimensions. The effects of the error sources are concluded to be negligible, the lenslet array is shown to be successfully aligned with the SLM, and other alignment applications are shown to be possible.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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