An adaptive joint transform correlator for real-time pattern recognition is presented. A reference image for the correlator is generated with a new iterative algorithm. The training algorithm is based on synthetic discriminant functions. The obtained reference image contains the information needed to reliably discriminate a target against known false objects and a cluttered background. Calibration lookup tables of all optoelectronics elements used are included in the design of the adaptive joint transform correlator. Two methods for the implementation of the proposed joint transform correlator in an optodigital setup are considered. Experimental results are provided and compared with those of computer simulations.
© 2006 Optical Society of America
Original Manuscript: January 3, 2006
Revised Manuscript: March 1, 2006
Manuscript Accepted: March 1, 2006
Victor H. Diaz-Ramirez, Vitaly Kober, and Josue Alvarez-Borrego, "Pattern recognition with an adaptive joint transform correlator," Appl. Opt. 45, 5929-5941 (2006)