An image-sensing device is disclosed, the image-sensing device comprising a multispectral sensor and a processor communicably coupled to the multispectral sensor. The processor is configured to determine an ambient light source classification based on a comparison of predefined spectral data to data corresponding to an output of the multispectral sensor. Also disclosed is a method of classifying an ambient light source by sensing a spectrum of light with a multispectral sensor; and determining an ambient light source classification based on a comparison of predefined spectral data to data corresponding to an output of the multispectral sensor. An associated computer program, computer-readable medium and data processing apparatus are also disclosed.

Devices and methods of the present technology utilize wavelength-dependent transmittance of 2D materials to identify the wavelength of an electromagnetic radiation. A wide range of 2D materials can be used, making possible the use of the technology over a large portion of the electromagnetic spectrum, from gamma rays to the far infrared. When combined with appropriate algorithms and artificial intelligence, the technology can identify the wavelength of one or more monochromatic sources, or can identify color through the use of a training set. When applied in an array format, the technology can provide color imaging or spectral imaging using different regions of the electromagnetic spectrum.

A data acquisition circuit board and an equipment monitoring system are provided. The data acquisition circuit board includes a power supply module configured to perform voltage conversion and supply a power supply signal; a micro-processing unit coupled to the power supply module; a data acquisition module coupled to the micro-processing unit; and a data transmission unit coupled to the power supply module and the micro-processing unit; wherein the micro-processing unit receives and processes data acquired by the data acquisition module, and outputs processed results to the data transmission unit, which transmits the processed results wirelessly.

A data acquisition circuit board and an equipment monitoring system are provided. The data acquisition circuit board includes a power supply module configured to perform voltage conversion and supply a power supply signal; a micro-processing unit coupled to the power supply module; a data acquisition module coupled to the micro-processing unit; and a data transmission unit coupled to the power supply module and the micro-processing unit; wherein the micro-processing unit receives and processes data acquired by the data acquisition module, and outputs processed results to the data transmission unit, which transmits the processed results wirelessly.

Method for selecting an elastic venous restraint orthosis intended to be slipped onto a lower limb of a patient. Acquisition of a photograph representing the skin of the limb and a calibration map including one or more calibration zones. The calibration map is placed on the limb in a position termed the “acquisition position.” Calibration of the photograph by the calibration zone or zones, in such a way that the representation of the skin on the photograph exhibits a calibrated colour. Selection, as a function of the calibrated colour, by computer and from a set of colours of a tone chart, of a tone chart colour, preferably of the tone chart colour closest to the calibrated colour, termed the “optimal colour,” and then determination, by computer, of an orthosis colour as a function of the tone chart colour selected. Selection of an orthosis exhibiting the orthosis colour.

Methods and systems for determining a radar compatible coating are provided. In one example, the method includes obtaining a reflectance measurement of a target coating to characterize a color of the target coating. One or more candidate formulas are generated to determine color matching to the color of the target coating. A corresponding color and a corresponding radar property for each of the one or more candidate formulations is predicted. A radar compatible coating composition that is the same or substantially similar in appearance to the target coating is generated. Generating the radar compatible coating composition is based at least in part on the corresponding color and the corresponding radar property for one of the one or more candidate formulations.

Disclosed are a system and techniques to determine a color of an optical fiber in a fiber optic cable. A spectrophotometer camera may obtain a color value of the optical fiber. A fiber adaptor is operable to hold a single optical fiber of a fiber optic cable in a field of view of the spectrophotometer camera. A memory storing instructions that, when executed by a processor, enable identifying a color of the optical fiber. The color value may be compared to a color value of a number of reference colors. A color match score value may be generated for the color value with respect to each reference color. A confidence value may be obtained for a pair of color match scores that are closest in score value. Based on the confidence value, one of the reference colors is identified as a color of the optical fiber.

A method of determining a color formula for a target color begins with generating a plurality of candidate color formulas to reproduce the target color. For each candidate formula, a predicted delta E indicating a difference from a predicted color for the candidate formula from the target color is determined. Also for each candidate formula, a confidence value in the predicted delta E is generated by summing weighted figures of merit for each colorant in the candidate formula. The weighting of the figures of merit represents each colorant's proportion in the candidate formula. A formula is then selected based on the predicted delta E and confidence value. The target color may be defined in terms of a multi-dimensional color space.

Disclosed herein is a computer-implemented method, a respective device, and a non-transitory computer-readable medium. The method includes: obtaining color values, texture values and digital images of a target coating, retrieving from a database one or more preliminary matching formulas based on the color and/or texture values obtained for the target coating, determining sparkle points within the respective obtained images and within the respective images associated with the one or more preliminary matching formulas, creating subimages of each sparkle point from the respective images, providing the created subimages to a convolutional neural network, the convolutional neural network being trained to correlate a respective subimage of a respective sparkle point with a pigment and/or pigment class, and determining, based on an output of the neural network, at least one of the one or more preliminary matching formulas as the formula(s) best matching the target coating.

A colorimetric system includes an acquiring unit that acquires a colorimetric value obtained by performing colorimetry by a colorimetric unit, a display processing unit that performs a process of displaying a comparison graphic obtained by combining a reference color graphic of a reference color region with a sample color graphic of a sample color region, and a comparison processing unit that compares a color value of a reference color set in the reference color region with a color value of a sample color set in the sample color region.