Implementation of a high-speed face recognition system that uses an optical parallel correlator

Abstract

We implement a fully automatic fast face recognition system by using a 1000 frame/s optical parallel correlator designed and assembled by us. The operational speed for the 1:N (i.e., matching one image against N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 s, including the preprocessing and postprocessing times. The binary real-only matched filter is devised for the sake of face recognition, and the system is optimized by the false-rejection rate (FRR) and the false-acceptance rate (FAR), according to 300 samples selected by the biometrics guideline. From trial 1:N identification experiments with the optical parallel correlator, we acquired low error rates of 2.6% FRR and 1.3% FAR. Facial images of people wearing thin glasses or heavy makeup that rendered identification difficult were identified with this system.

Fuzzy logic and optical correlation-based face recognition method for patient monitoring application in home video surveillance

“…7 However, even if these techniques are interesting, they are generally too complicated to achieve with an all-optical system, especially for reconfigurable systems. [7][8][9][10][11][12][20][21][22][23][24][25] Hybrid methods (optical/digital) have been developed to alleviate problems associated with optical implementation, such as the need to use several spatial light modulators and the alignment problem of the optical elements. The potential of the optical correlation methods has been recognized because they possess a strong discriminating ability [7][8][9][10][11][12][20][21][22][23][24][25] and robustness with respect to noise.…”

“…Utilization of the VLC for face recognition has been fairly popular. [6][7][8][9][10][11][12][20][21][22][23] This method appears very effective despite possible distortions that may exist between the target face and the reference images due to vertical and horizontal rotations. Hence, we must have a large number of references leading a large number of filters.…”

“…[7][8][9][10] Here the procedure is described for a single camera. However, because the main purpose here is to record the parameters related to a moving subject, we need to introduce a 3-D tracking of the subject.…”

“…Face recognition is easily achieved with a camera; however, it can be affected by several potential problems, such as ambient illumination conditions and facial expression. 10 We start by reducing the face area in the target scene to get a small-size image with very little background noise. This is done by segmenting the scene using a subject's skin detection method based on the hue, saturation, and value (HSV) color space.…”

Cellular phone face recognition system based on optical phase correlation

“…The vanderLugt Correlator (VLC) was proposed in 1964 as a basic optical correlator [6], and the face recognition engine Fast Face Recognition Optical Correlator (FARCO) based on VLC was developed in 2004 [7]. In this face recognition engine, a correlation filter is designed to improve recognition accuracy using optical correlation [8], the system is configured using fast devices, and appropriate preprocessing is applied to facial images.…”