We propose a compact, passive optical limiter incorporating nonlinear materials in a multi-layer photonic bandgap (PBG) structure. A coupled-mode theory that includes interaction between counter-propagating optical pulses and diffraction describes the complex transmission and reflection coefficients. Two materials with different nonlinear refraction and absorption coefficients make up the individual layers. Transverse modulational instabilities appear as the intensity increases; this effect is exploited to improve the optical limiter performance by inserting an aperture in the system. Investigating the role that material combinations play in determining the transmission characteristics optimizes the device design. Our results indicate that PBG devices can improve the dynamic range by more than a factor of two over homogeneous material designs.
Optical fingerprint security verification is gaining popularity, as it has the potential to perform correlation at the speed of light. With advancement in optical security verification techniques, authentication process can be almost foolproof and reliable for financial transaction, banking, etc. In law enforcement, when a fingerprint is obtained from a crime scene, it may be blurred and can be an unhealthy candidate for correlation purposes. Therefore, the blurred fingerprint needs to be clarified before it is used for the correlation process. There are a several different types of blur, such as linear motion blur and defocus blur, induced by aberration of imaging system. In addition, we may or may not know the blur function. In this paper, we propose the non-singularity inverse filtering in frequency/power domain for deblurring known motion-induced blur in fingerprints. This filtering process will be incorporated with the pow spectrum subtraction technique, uniqueness comparison scheme, and the separated target and references planes method in the joint transform correlator. The proposed hardware implementation is a hybrid electronic-optical correlator system. The performance of the proposed system would be verified with computer simulation for both cases: with and without additive random noise corruption.
A new joint wavelet transform correlation based technique is proposed for feature extraction such as detection of edges in an unknown input scene. We exploited a modified version of the Roberts and Sobel wavelet filters as the reference images for extracting the edges of an unknown input scene. The performance of the proposed technique using the aforementioned wavelet filters are evaluated and compared using numerical simulations.