Modulation-encoded light, using different spectral bin coded light components, can illuminate a stationary or moving (relative) target object or scene. Response signal processing can use information about the respective different time-varying modulation functions, to decode to recover information about a respective response parameter affected by the target object or scene. Electrical or optical modulation encoding can be used. LED-based spectroscopic analysis of a composition of a target (e.g., SpO2, glucose, etc.) can be performed; such can optionally include decoding of encoded optical modulation functions. Baffles or apertures or optics can be used, such as to constrain light provided by particular LEDs. Coded light illumination can be used with a focal plane array light imager receiving response light for inspecting a moving semiconductor or other target. Encoding can use orthogonal functions, such as an RGB illumination sequence, or a sequence of combinations of spectrally contiguous or non-contiguous colors.

Disclosed is a switch device including a push operation part having a light transmitting portion, a control board installed in a push operation direction of the push operation part, a fingerprint sensor provided on the push operation part to detect a fingerprint of a user pushing the push operation part, a controller provided on one surface of the control board to control the fingerprint sensor, a flexible board provided to electrically connect the fingerprint sensor and the controller, and a plurality of light sources installed on opposite surfaces of the control board and closer to the push operation part than the controller to illuminate the light transmitting portion.

An optical dimensioning system includes one or more light emitting assemblies configured to project one or more predetermined patterns on an object; an imaging assembly configured to sense light scattered and/or reflected off the object, and to capture an image of the object while the patterns are projected; and a processing assembly configured to analyze the image of the object to determine one or more dimension parameters of the object. The light emitting assembly may include a single piece optical component configured for producing a first pattern and second pattern. The patterns may be distinguishable based on directional filtering, feature detection, feature shift detection, or the like. A method for optical dimensioning includes illuminating an object with at least two detectable patterns; and calculating dimensions of the object by analyzing pattern separate of the elements comprising the projected patterns. One or more pattern generators may produce the patterns.

An optical dimensioning system includes one or more light emitting assemblies configured to project one or more predetermined patterns on an object; an imaging assembly configured to sense light scattered and/or reflected off the object, and to capture an image of the object while the patterns are projected; and a processing assembly configured to analyze the image of the object to determine one or more dimension parameters of the object. The light emitting assembly may include a single piece optical component configured for producing a first pattern and second pattern. The patterns may be distinguishable based on directional filtering, feature detection, feature shift detection, or the like. A method for optical dimensioning includes illuminating an object with at least two detectable patterns; and calculating dimensions of the object by analyzing pattern separate of the elements comprising the projected patterns. One or more pattern generators may produce the patterns.

A vehicle detecting device includes: a camera that includes an image sensor and a first filter, the image sensor including a plurality of imaging elements including a first imaging element group and a second imaging element group, the first filter keeping an amount of light entering the first imaging element group lower than an amount of light entering the second imaging element group; an image generating unit that generates a first image based on information obtained from the first imaging element group and a second image based on information obtained from the second imaging element group; and a detecting unit that detects a front vehicle based on the first image and the second image.

Methods and apparatuses for detecting characteristics of a card include a method for identifying a card containing foil, the foil detection method comprising converting an image file depicting a card into a hue, saturation, value (“HSV”) colour space, applying a value mask to exclude a group of pixels from analysis that do not form an intensified brightness area, and comparing the number of remaining pixels against a threshold to determine whether the card contains foil. In another aspect, a method for assigning a condition grading to a card comprises converting an image file depicting a diffusely illuminated card into an HSV colour space, isolating a uniform portion of the converted image file, applying a value mask to the converted image file to exclude pixels forming an undamaged portion of the card, and comparing the number of remaining pixels to a plurality of grading thresholds to assign a condition grading.

The present invention provides a processing apparatus (10) including an acquisition unit (11) that acquires an image including a product, a detection unit (12) that detects, from the image, a target region being a region including an observation target, a computation unit (13) that computes an evaluation value of an image of the target region, and a registration unit (14) that registers the image as an image for learning, when the evaluation value satisfies a criterion.

The present invention provides a processing apparatus (10) including an acquisition unit (11) that acquires an image including a product, a detection unit (12) that detects, from the image, a target region being a region including an observation target, a computation unit (13) that computes an evaluation value of an image of the target region, and a registration unit (14) that registers the image as an image for learning, when the evaluation value satisfies a criterion.

A method of controlling parameters for image sensors includes; receiving a first image and a second image, calculating first feature values related to the first image and second feature values related to the second image; generating comparison results by comparing the first feature values of fixed regions and first variable regions of the first image with the second feature values of fixed regions and first variable regions of the second image, and controlling at least one parameter on the basis of the comparison results.

A method of controlling parameters for image sensors includes; receiving a first image and a second image, calculating first feature values related to the first image and second feature values related to the second image; generating comparison results by comparing the first feature values of fixed regions and first variable regions of the first image with the second feature values of fixed regions and first variable regions of the second image, and controlling at least one parameter on the basis of the comparison results.