A method of determining a peak intensity in an optical spectrum is described. The method includes producing a two-dimensional array of spectrum values by imaging the optical spectrum onto a detector array. An offset using an actual location and an expected location of a peak of an interpolated subarray is used to adjust an expected location of another peak that is within another two-dimensional subarray. Interpolated spectrum values are then used to produce a peak intensity value of the second peak.

In one aspect, a hyperspectral image measurement device is provided to include: a main body; an illumination module disposed in the main body and including LEDs having different peak wavelengths to irradiate light to a subject; a camera disposed on the main body and receiving light reflected from the subject to acquire an image of the subject; a barrel having a contact surface contacting the subject, the contact surface located to be spaced apart from the illumination module and the camera module by a predetermined distance; and a reference cover located on the contact surface and including a standard reflection layer for reflecting light irradiated from the illumination module toward the camera module.

The invention relates to a method for identifying one or more spectral features in a spectrum (4, 5) of a sample for a constituent analysis of the sample, comprising providing the spectrum (4, 5), predefining an approximation function (6), which is a continuously differentiable mathematical function, respectively forming an (n−1)-th order derivative (7, 8, 9) of the spectrum (4, 5) and of the approximation function (6), wherein the number n>1, generating a correlation matrix (10) from the two (n−1)-th order derivatives (7, 8, 9), and respectively identifying the spectral feature or one of the spectral features in each case as a function of a local extremum (i) of the correlation matrix (10) for at least one extremum (i) of the correlation matrix (10) in order to simplify the constituent analysis of the sample.

An optical filter includes: a first filter including a pair of first reflective films facing each other via a first gap and a first actuator changing a gap between the pair of first reflective films; and a second filter including a pair of second reflective films facing each other via a second gap and a second actuator changing a gap between the pair of second reflective films with the pair of second reflective films disposed on an optical path of light transmitted through the pair of first reflective films, in which each of the first reflective film and the second reflective film is configured by a plurality of optical bodies being laminated, the optical body has reflection characteristics of reflecting light centered on a predetermined design center wavelength, and the design center wavelength is different in each of the optical bodies.

The invention relates to a method for identifying one or more spectral features in a spectrum (4, 5) of a sample for a constituent analysis of the sample, comprising providing the spectrum (4, 5), predefining an approximation function (6), which is a continuously differentiable mathematical function, respectively forming an (n−1)-th order derivative (7, 8, 9) of the spectrum (4, 5) and of the approximation function (6), wherein the number n>1, generating a correlation matrix (10) from the two (n−1)-th order derivatives (7, 8, 9), and respectively identifying the spectral feature or one of the spectral features in each case as a function of a local extremum (i) of the correlation matrix (10) for at least one extremum (i) of the correlation matrix (10) in order to simplify the constituent analysis of the sample.

A discharge detection system includes a plurality of optical fibers having different optical distances from each other and provided to allow discharge light generated from a test object to enter at least one of the optical fibers, an optical sensor configured to detect the discharge light having entered the at least one of the optical fibers and to output a detection signal having a temporal change in an amplitude of the detection signal, the temporal change in the amplitude corresponding to a temporal change in intensity of the discharge light, and a signal processing system configured to identify an area where the discharge light is generated based a point of time of at least one peak in the detection signal.

In accordance with particular implementations of the invention described herein, a sample for analysis is illuminated under each of one or more narrow-band light sources. The light incident upon this sample is received by a sensor that generates measurement data in response thereto. One or more processors are configured to receive the measurement data and derive an excitation response curve and a fluorescent response curve from the measurement data. The processor is further configured to generate a fluorescent profile value using measurements from the fluorescent response curve for each of the captured narrow band measurement data and an excitation profile value corresponding to the area under the fluorescence curve divided by the area under the excitation curve. The generated fluorescent profile and excitation profile are both output as a dataset providing improved measurement values over similar approaches in the art.

A method and apparatus for determining a level of background fluorescent light produced during photometric interrogation of a sample is provided. The method includes applying an excitation light to a sample using a laser at a plurality linewidths different from one another, the excitation light at each of the plurality of different linewidths applied at an excitation wavelength operable to cause emission of light from the sample, the light emitted from the sample including Raman scattered light and background fluorescent light; detecting light emitted from the tissue sample at each of the plurality of linewidths using a detector and producing light signals representative of the detected light; and determining a level of the background fluorescent using the light signals representative of the detected light for each of the plurality of different linewidths.

There is provided a learning method. The method includes performing preprocessing on light emission data in a chamber of a plasma processing apparatus, setting a constraint for generating a regression equation representing a relationship between an etching rate of the plasma processing apparatus and the light emission data, selecting a learning target wavelength from the light emission data subjected to the preprocessing, and receiving selection of other sensor data different from the light emission data. The method further includes generating a regression equation based on the set constraint while using, as learning data, the selected wavelength, the received other sensor data, and the etching rate, and outputting the generated regression equation.

A method for the determination and correction of background signals in a spectrum, consisting of signals of a plurality of spectral points, characterized by the steps of: Calculating at least three statistic or analytic functions of the signal values of the spectrum, attributing probabilities P.sub.i(band) for the presence of bands to each point in each of the calculated functions: Adding the probabilities P.sub.i(band) up to an overall probability P.sub.i(band) from all calculated functions for each point; calculating a probability P(background) for the presence of background for each point in the spectrum from said overall probability P.sub.i(band) according to P(background)=1P.sub.i(band) wherein negative values are set to zero; and calculating a fit of the signal values at all points of the original spectrum wherein the signal in each point is taken into account in the fit only with the respective probability for the presence of background P(background), and subtraction of the background function determined in such a way from the signal values of the original spectrum in order to generate a background corrected spectrum.