A method for true-to-sample measurement by a mobile ingredient analysis system having a housing with a window, an interface for an external reference unit, a display and operating unit, a light source, an optical spectrometer, a camera, an internal reference unit, and an electronic control unit. The method includes: selecting a calibration product suitable for a sample to be examined; performing a plausibility check of the calibration product, an incorrect selection being signaled and an alternative calibration product being selected; outputting measurement conditions comprising the measurement point to be selected and measurement duration for the selected calibration product; capturing measured values of the sample by the spectrometer under the measurement conditions and with simultaneous monitoring of the measurement conditions; processing the captured measured values by means of an electronic control unit, each measured value captured while the measurement conditions were met being declared valid; outputting the measured values deemed valid.

There is provided an apparatus (100) comprising one or more processors (102) configured to acquire a multi-/hyperspectral two-dimensional image of an object at respective wavelengths. For at least one pixel of the image corresponding to a first point on an object surface, a set of intensity values for said at least one pixel is compared to a characteristic curve to determine a similarity measure. A first angle of the first point is estimated from the similarity measure or a correction is applied to the image at the first point using the similarity measure. The characteristic curve is a difference between a spectrum of at least one second point on the object surface at a second angle with respect to a plane of the image and a spectrum of at least one third point on the object surface at a third angle with respect to the plane of the image.

A system for remote-controlling a spectrometer, which includes: at least one spectrometry device including a spectrometer and auxiliary modules, the spectrometry device being configured to measure spectrometry data on an object and/or a process; a control device configured to control the spectrometry device, the control device including an element for controlling the spectrometry device, an element for acquiring and processing the spectrometry data, and an element for remote communication; and at least one interface modules configured to communicate with the control device remotely. The remote-control device is configured to communicate with the interface module via Internet, and the spectrometry device is interchangeable. Also, a device for remote-controlling a spectrometry system that is configured to be used in a system for remote-controlling the spectrometer.

In some implementations, a device may identify, based on spectroscopic data, a pseudo steady state end point indicating an end of a pseudo steady state associated with the blending process. The device may identify a reference block and a test block from the spectroscopic data based on the pseudo steady state end point. The device may generate a raw detection signal associated with the reference block and a raw detection signal associated with the test block. The device may generate a statistical detection signal based on the raw detection signal associated with the reference block and the raw detection signal associated with the test block. The device may determine whether the blending process has reached a steady state based on the statistical detection signal.

An optical system includes a multispectral sensor; an optical filter including a plurality of optical channels that is disposed over the multispectral sensor; and a lens that is disposed over the optical filter. The lens is configured to direct first light that originates from a scene to the optical filter. The optical filter is configured to pass one or more portions of the first light to the multispectral sensor. The multispectral sensor is configured to generate, based on the one or more portions of the first light, spectral data associated with the scene.

A spectroscopic metrology system includes a spectroscopic metrology tool and a controller. The controller generates a model of a multilayer grating including two or more layers, the model including geometric parameters indicative of a geometry of a test layer of the multilayer grating and dispersion parameters indicative of a dispersion of the test layer. The controller further receives a spectroscopic signal of a fabricated multilayer grating corresponding to the modeled multilayer grating from the spectroscopic metrology tool. The controller further determines values of the one or more parameters of the modeled multilayer grating providing a simulated spectroscopic signal corresponding to the measured spectroscopic signal within a selected tolerance. The controller further predicts a bandgap of the test layer of the fabricated multilayer grating based on the determined values of the one or more parameters of the test layer of the fabricated structure.

Systems for measuring optical properties of a specimen are disclosed. The systems are configured to sample signals related to the measurement of the properties of a specimen, and perform software-based coherent detection of the signals to generate resulting measurements are based on the signals acquired at substantially the same time instance. This facilitates the displaying or generating of the desired measurements in real time. In one configuration, the system is configured to direct a modulated light signal at a selected wavelength incident upon a specimen. In another configuration, the system is configured to direct a combined light signal, derived from a plurality of light signals at different wavelengths and modulated with different frequencies, incident upon a specimen. In yet another configuration, the system is configured to direct a plurality of light signals modulated with different frequencies incident upon different regions of a specimen.

A multispectral sensor device may include a sensor array comprising a plurality of channels and one or more processors to determine that a time-sensitive measurement is to be performed, wherein the time-sensitive measurement is to be performed using data collected by one or more channels of the plurality of channels; cause the data to be collected by a proper subset of channels, of the plurality of channels, wherein the proper subset of channels includes the one or more channels; and determine the time-sensitive measurement based on the data.

An object recognition apparatus includes a first spectrometer configured to obtain a first type of spectrum data from light scattered, emitted, or reflected from an object; a second spectrometer configured to obtain a second type of spectrum data from the light scattered, emitted, or reflected from the object, the second type of spectrum data being different from the first type of spectrum data; an image sensor configured to obtain image data of the object; and a processor configured to identify the object using data obtained from at least two from among the first spectrometer, the second spectrometer, and the image sensor and using at least two pattern recognition algorithms.

An electronic device and a method for spectral model explanation are provided. The method includes: obtaining first labeled spectral data; storing a plurality of pipelines, selecting a selected pipeline from the pipelines, and generating a first measurement result corresponding to the first labeled spectral data according to the selected pipeline; and determining an important wavelength range corresponding to the selected pipeline according to the first measurement result.