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.

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We measured the time variation of a received laser signal level during snowfall over a distance of 72 m. The signal level dropped sharply for up to 10 ms when a snowflake crossed the laser beam. The probability distribution of the variation due to snowfall was calculated by assuming it to be the linear superposition of the light diffracted by snowflakes. The measured distributions could be reproduced by assuming reasonable snowflake size distributions. Furthermore, the probability distributions due to snowfall over a 1 km distance were calculated, and the expected bit errors during snowfall and the transmitted beam sizes were evaluated.

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.

Faint Object Camera and Spectrograph (FOCAS) is a versatile common-use optical instrument for the 8.2m Subaru Telescope, offering imaging and spectroscopic observations. FOCAS employs grisms with resolving powers ranging from 280 to 8200 as dispersive optical elements. A grism is a direct-vision grating composed of a transmission grating and prism(s). FOCAS has five grisms with replica surface-relief gratings including an echelle-type grism, and eight grisms with volume-phase holographic (VPH) gratings. The size of these grisms is 110 mm×106 mm in aperture with a maximum thickness of 110 mm. We employ not only the dichromated gelatin, but also the hologram resin as a recording material for VPH gratings. We discuss the performance of these FOCAS grisms measured in the laboratory, and verify it by test observations, and show examples of astronomical spectroscopic observations.