A light distribution controller includes a computation unit that extracts an index value from a predetermined region to be processed within an image, a pattern determiner that determines a light distribution pattern such that the index value approaches a maximum value, and a lamp controller that controls a light distribution variable lamp so as to form the light distribution pattern. The index value is at least one of a mean intensity of HOG feature values of a plurality of pixels of the region to be processed or an edge gray level proportion indicating, in a local binary pattern (LBP) histogram of the plurality of pixels, a proportion of the number of pixels belonging to a gray level of an edge portion to a total number of the plurality of pixels.

Provided are computer-implemented technologies of authenticating documents. The technologies use a set of photo images (or videos), taken under a certain illumination condition and from a set of distinct tilting angles, on one or more security/ID features of one or more documents of a document genre whose authenticity is ascertained, to train an Artificial Intelligence (AI) machine learning program to build a learned model. The learned model, through the said training, attains a set of angular responses of the document genre under the illumination condition which encode a set of descriptive information about each of the one or more security/ID features of the document genre under the illumination condition. The learned model, then, is applied to authenticate, one by one, a number of target documents of the document genre whose authenticity is unknown and to be determined.

Provided are computer-implemented technologies of authenticating documents. The technologies use a set of photo images (or videos), taken under a certain illumination condition and from a set of distinct tilting angles, on one or more security/ID features of one or more documents of a document genre whose authenticity is ascertained, to train an Artificial Intelligence (AI) machine learning program to build a learned model. The learned model, through the said training, attains a set of angular responses of the document genre under the illumination condition which encode a set of descriptive information about each of the one or more security/ID features of the document genre under the illumination condition. The learned model, then, is applied to authenticate, one by one, a number of target documents of the document genre whose authenticity is unknown and to be determined.

An electronic apparatus includes a processor configured to identify a first distance based on locations of first pixels that received the reflective light, and identify a second distance based on locations of the second pixels that received the reflective light, and calculate a difference between the first and second distances, and based on a distance acquired by the calculation and a moving distance of the electronic apparatus identified through the second sensor, identify whether the reflective light is reflective light reflected by an object or reflective light that was reflected on the object and then reflected again by another object.

A method includes: (a) executing prior learning of the machine learning model, using simulation data of an object; (b) capturing a first image of the object from a first direction of image capture; (c) recognizing a first position and attitude of the object from the first image, using the machine learning model already learned through the prior learning; (d) performing a correctness determination about the first position and attitude; (e) capturing a second image of the object from a second direction of image capture that is different from the first direction of image capture when it is determined that the first position and attitude is correct, then converting the first position and attitude according to a change from the first direction of image capture to the second direction of image capture and thus calculating a second position and attitude, and assigning the second position and attitude to the second image and thus generating training data; and (f) changing an actual position and attitude of the object and repeating the (b) to (e).

A method includes: (a) executing prior learning of the machine learning model, using simulation data of an object; (b) capturing a first image of the object from a first direction of image capture; (c) recognizing a first position and attitude of the object from the first image, using the machine learning model already learned through the prior learning; (d) performing a correctness determination about the first position and attitude; (e) capturing a second image of the object from a second direction of image capture that is different from the first direction of image capture when it is determined that the first position and attitude is correct, then converting the first position and attitude according to a change from the first direction of image capture to the second direction of image capture and thus calculating a second position and attitude, and assigning the second position and attitude to the second image and thus generating training data; and (f) changing an actual position and attitude of the object and repeating the (b) to (e).

A tunable light projector including a light source, a fixed optical phase modulator, and a tunable liquid crystal panel is provided. The light source is configured to emit a light beam, and the fixed optical phase modulator is disposed on a path of the light beam and configured to modulate phases of the light beam. The tunable liquid crystal panel is disposed on the path of the light beam and configured to be switched between a plurality of states, wherein the plurality of states include a lens array state in which the tunable liquid crystal panel comprises a lens array.

A tunable light projector including a light source, a fixed optical phase modulator, and a tunable liquid crystal panel is provided. The light source is configured to emit a light beam, and the fixed optical phase modulator is disposed on a path of the light beam and configured to modulate phases of the light beam. The tunable liquid crystal panel is disposed on the path of the light beam and configured to be switched between a plurality of states, wherein the plurality of states include a lens array state in which the tunable liquid crystal panel comprises a lens array.

The present invention relates biometric authentication using an optical biometric arrangement comprising an image sensor comprising a photodetector pixel array configured to capture an image of an object, the image sensor being arranged under a controllable light source comprising light source units, the method comprising: providing a light pattern comprising portions of different light intensity for illuminating the object; acquiring an image of the object, the image comprising image portions corresponding to the portions of different light intensity of the light pattern illuminating the object, at least one image portion being captured by pixels in he photodetector pixel array arranged directly under a light source unit being active during image acquisition, and at least one image portion being captured by pixels in the photodetector pixel array arranged under an at least partly in-active illumination area of the controllable light source during image acquisition, performing biometric authentication at least partly based on metrics extracted from the image portions.

The present invention relates biometric authentication using an optical biometric arrangement comprising an image sensor comprising a photodetector pixel array configured to capture an image of an object, the image sensor being arranged under a controllable light source comprising light source units, the method comprising: providing a light pattern comprising portions of different light intensity for illuminating the object; acquiring an image of the object, the image comprising image portions corresponding to the portions of different light intensity of the light pattern illuminating the object, at least one image portion being captured by pixels in he photodetector pixel array arranged directly under a light source unit being active during image acquisition, and at least one image portion being captured by pixels in the photodetector pixel array arranged under an at least partly in-active illumination area of the controllable light source during image acquisition, performing biometric authentication at least partly based on metrics extracted from the image portions.