A public area defense system, comprising a non-lethal reactive deterrence defense subsystem, an optical subsystem operably coupled to and in communication with the non-lethal reactive deterrence defense subsystem, and an acoustic subsystem operably coupled to and in communication with the non-lethal reactive deterrence defense subsystem. The public area defense system may further comprise a computer system in communication with each of the non-lethal reactive deterrence defense subsystem, the optical subsystem, and the acoustic subsystem, wherein each of the non-lethal reactive deterrence defense subsystem, the optical subsystem, and the acoustic subsystem are operable to interact with an actor

An identification module is disclosed for use in a key making machine. The identification module may have a key receiving assembly configured to receive only a shank of an existing key. The identification module may also have a tip guide, configured to receive a tip of the shank of the existing key. The tip guide may have a slot that exposes a tip end of the shank. The identification module may also have an imaging assembly configured to capture an image of the tip end through the slot.

Devices and methods for visibly highlighting areas of a region including an imager configured to image the region with a sensitivity to at least one of wavelength, light level, or contrast greater than the human eye, an overlay element configured to visibly highlight areas of the region and registered to the imager to produce alignment of imaged features with highlighted features at the same location on the region, and at least one of a controller executing a program or logic configured to process acquired images from the imager to identify areas of the region determined not visible to the human eye, and control the overlay element to visibly highlight those areas on the region.

Systems and methods are described, including a system (100) for automatically ascertaining a height characteristic of a contaminant (104) on a travel surface (102). The system (100) comprises an illumination and imaging device (106). At a first time, when the travel surface (102) is generally free of contaminant, the illumination and imaging device (106) illuminates the travel surface (102) with at least one light beam (119), and images at least one impingement of the at least one light beam (119). At a second time, when the travel surface (102) is covered by a layer of contaminant (104), the illumination and imaging device (106) illuminates the travel surface with a light beam (132), and images an impingement of the light beam on an impingement surface (107). In response to the imaging, a computer (130) calculates the height characteristic of the contaminant. Other embodiments are also described.

The present invention is to non-invasively, objectively, and quantitatively identify a temporal filter associated with visual function by using an eye movement. According to the invention, an initial image having a constant luminance in an entirety of the initial image, a first stimulus pattern having a mean luminance that is the same as that of the initial image, and a second stimulus pattern that induces an apparent motion in conjunction with the first stimulus pattern are presented in this order. Eye movement is measured in a period of time while the second stimulus pattern is being presented. Also, the eye movement is associated with presentation time length of the first stimulus pattern and then stored. In this process, parameters of the motion energy model are optimized so that a difference between a measurement waveform identified by the change in eye position and by the presentation time length associated with the change in eye position and the simulation result is minimized and thereby the temporal filter that is specific to the subject is calculated.

A biological information detection method including: causing a light source to emit first light in a first area; detecting a presence of a first living body in the first area based on a second light which is resulted in the emission of the first light; detecting body motion of the first living body based on the second light; determining whether or not the body motion is within a low level; notifying, in response to the determination that the body motion is within the low level, a first alert to the first living body, where the first alert includes an information to draw attention of the first living body.

In one embodiment, a method of machine learning and/or image processing for spectral object classification is described. In another embodiment, a device is described for using spectral object classification. Other embodiments are likewise described.

Described herein is an imaging system (200) for a driver monitoring system (100). The imaging system (200) includes a light source (108) for generating an input light beam (202) and projecting the input light beam (202) along a path towards a driver (102) of a vehicle. System (200) also includes a dielectric metasurface (201) positioned within the path of the input light beam (202). The metasurface (201) has a two dimensional array of surface elements configured to impose predetermined phase, polarization and/or intensity changes to the input light beam (202) to generate an output light beam (204) for illuminating the driver (102). System (200) further includes an image sensor (106) configured to image reflected light (208) being light from the output light beam (204) that is reflected from the driver.

A polarized image acquisition section 11a acquires a polarized image of a target object having one or more polarization directions. A polarization parameter acquisition section 12-1 calculates the average brightness α of a polarization model on the basis of a non-polarized image subjected to sensitivity correction. Further, the polarization parameter acquisition section 12-1 calculates the amplitude β of the polarization model on the basis of the calculated average brightness α, pre-stored information regarding the zenith angle θ of the normal line of the target object, a refractive index r, and reflectance property information indicative of whether a subject is diffuse reflection or specular reflection. A polarization model detection section 13-1 is able to detect the polarization properties of the target object through the use of an image polarized in one or more polarization directions, by calculating the phase ϕ of the polarization model on the basis of a polarized image of the target object having one or more polarization directions, the average brightness α, and the amplitude β of the polarization model.

A process for detecting foreign objects in a food-containing product stream comprises: forwarding the product stream, illuminating the product stream, generating raw data based on electromagnetic energy reflected from the product stream using a camera, and processing the raw data to generate classified image data corresponding with food product, foreign object(s), and background. A system for detecting foreign objects in the product stream comprises a forwarding device, an illuminator, a camera, and instructions in memory that form image data and classify the data as corresponding with food product, foreign objects, and background.