Facial recognition by a compact parallel optical correlator

Abstract

With the progress of information technology, the need for an accurate personal identification system based on biological characteristics is increasing the demand for this type of security technology instead of conventional systems using ID cards or pin numbers. Among other features, the face is the most familiar element and is less subject to psychological resistance. As a simple and compact recognition system satisfying the required performance, we implemented a hybrid system based on the optical recognition principle using a multi-level zone plate as a Fourier-transform lens and we report the preliminary results of their application to face recognition. In this paper, we present the design procedure and fabrication process for an improved version of a second-generation compact parallel correlator (named COPaC II), the size of which is 20 × 24 × 43 cm3 and weight 6 kg. As a result, we obtained a low error rate of 0% as the false match rate and 0.3% as the false non-match rate, thus the COPaC II significant identification security level is sufficiently stable. With the aim of further enhancing the throughput and robustness, we conducted performance tests where the system is used as a computer log-in device and as a pre-screening device for crime investigation. In both experiments, a high rate of successful recognition, such as 90% recognition and 94% rejection rate for log-in, was obtained. Experiments on twins to check the disguise recognition, and on the effects of changes in brightness and arbitrary size of images to test its robustness are also included.

Proposal of meta‐data in a database for identification using face images

“…A small-sized optical parallel correlator (COPaC) with a size of 15 × 23 × 6.3 cm 3 and a weight of 4 kg was designed and fabricated. The precision of the device was investigated for images of 300 subjects taken on the same day, and high accuracy was verified, with a false nonmatch rate of 0% and a false match rate of 0.3% [8,14]. Using the above highly accurate recognition system, a verification experiment was performed.…”

A study of multibiometric traits of identical twins

“…6,7,11 A verification experiment with 10 sets of identical twins was performed using a 2D face recognition system; the experiment consisted of enrolling one of the twins, and asking the other to try to log into the system. On this small database, the rejection threshold was always satisfied, leading to a rejection of all the impostor twins.…”

“…Some experiments show that face and voice 6,7 can be used to distinguish identical twins. Due to the difficulty in obtaining a large biometric database of identical twins, most experiments are performed on small databases, making the conclusions less reliable.…”

Face recognition based on texture information and geodesic distance approximations between multivariate normal distributions

“…Moreover, the image processing and computer vision fields may be used to help to extract reliable features for several instrumentation-related applications which use texture information, such as face recognition [1][2][3][4], brain image recognition [5,6], texture recognition of material images [7], food image recognition [8,9], character recognition [10,11], yawning detection [12], etc. In this work, we are mainly interested in face recognition by using efficient texture dissimilarity metrics based on geodesic distance approximations between probability distributions.…”