An image-encrypted joint transform correlator for pattern recognition is proposed and evaluated. The correlator performs twofold correlation for recognizing the primary image and cipher, and the encrypting cipher acts to enhance or inhibit the correlation peak if the cipher is correctly input. By incorporating the original image with an appropriate cipher, the correlator achieves better pattern discrimination and is robust against distortion. Simulation results show that the pixel number and the cell size of cipher affect the characteristics of the correlator.
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics