Abstract: A calibration curve creating method includes: (a) acquiring observation data of a plurality of samples of a test object; (b) acquiring content of a target component of each sample; (c) estimating a plurality of independent components when the observation data of each sample is separated into the plurality of independent components, and acquiring a mixing coefficient corresponding to the target component for each sample; and (d) acquiring a regression equation of a calibration curve. (c) includes acquiring an independent component matrix by performing a first preprocessing including normalization of the observation data, a second preprocessing including whitening, and an independent component analysis process in this order. ? divergence is used as an independence index of the independent component analysis process, and a robust regression method is used in (d).

Abstract: A calibration curve generation device includes an estimation unit that estimates a plurality of independent components or main components constituting observation spectral data of a plurality of samples and a regression formula calculation unit that acquires a regression formula of a calibration curve based on glucose concentration of the plurality of samples and a mixing coefficient of the independent components or the main components in the observation spectral data for each of the samples. The estimation unit selects a component waveform signal having a peak in a wavelength selected in advance as the independent components or the main components.

Abstract: A calibration curve generation method includes acquiring an independent component matrix including independent components of each sample the independent component matrix by performing first pre-processing that includes normalizing observation data, second pre-processing that includes whitening, and independent component analysis processing in order. Further, the same noise is added to the observation data related to a plurality of samples in the first pre-processing.

Abstract: A target component calibration device includes a mixing coefficient calculating section that calculates mixing coefficients of target components regarding a test object based on observational data regarding the test object and calibration data, and a target component content calculating section that calculates the content of target components based on the mixing coefficients calculated by the mixing coefficient calculating section and a simple regression equation representing the relationship between the content and the mixing coefficients corresponding to the target components. The target component content calculating section adjusts at least one of two constants of the simple regression equation depending on a measurement condition when the observational data is obtained.

Abstract: A calibration curve creation method includes a step of obtaining an independent component matrix including independent components of each sample, and this step includes a step of obtaining the independent component matrix by performing a first preprocess including normalization of the observation data, a second preprocess including whitening, and independent component analysis in this order. In the first preprocess, normalization is performed after a process based on project on null space (PNS) is performed. In the PNS, as a single-variable function representing a variation which depends on an ordinal number ? (where ? is an integer from 1 to N) of a data length N of the observation data, not a power function of ? with an exponent of an integer but a single-variable function which monotonously increases according to an increase in ? in a range of the value of ? from 1 to N is used.

Abstract: An estimation device is configured to estimate a feature value of a specific component contained in a sample and includes: a spectral estimation parameter storage module; a calibration parameter storage module; a multiband image acquirer; an optical spectrum operator configured to compute an optical spectrum from a multiband image using a spectral estimation parameter; and a calibration processor configured to compute the feature value from the optical spectrum using a calibration parameter.

Abstract: A calibration curve creating method includes: (a) acquiring observation data of a plurality of samples of a living body, when near infrared light is emitted to the living body and an absorbance spectrum obtained from transmitted light or diffusely-reflected light thereof is set as the observation data; (b) acquiring content of a target component of each sample; (c) estimating a plurality of independent components when the observation data of each sample is separated into the plurality of independent components, and acquiring a mixing coefficient corresponding to the target component for each sample; and (d) acquiring a regression equation of a calibration curve. (c) includes acquiring an independent component matrix by performing processes of normalization, whitening, and independent component analysis of the observation data, and the normalization is performed after a process performed by project on null space.

Abstract: A calibration curve creating method includes: (a) acquiring observation data of a plurality of samples of a test object; (b) acquiring content of a target component of each sample; (c) estimating a plurality of independent components when the observation data of each sample is separated into the plurality of independent components, and acquiring a mixing coefficient corresponding to the target component for each sample; and (d) acquiring a regression equation of a calibration curve. (c) includes acquiring an independent component matrix by performing a first preprocessing including normalization of the observation data, a second preprocessing including whitening, and an independent component analysis process in this order. ? divergence is used as an independence index of the independent component analysis process, and a robust regression method is used in (d).

Abstract: A calibration curve creation method is capable of performing accurate measurement from a piece of observation data. The calibration curve creation method includes (a) acquiring observation data regarding a plurality of samples of a subject, (b) acquiring the content of a target component in each sample, (c) estimating a plurality of independent components at the time of separation into a plurality of independent components of each sample and calculating a mixing coefficient corresponding to the target component for each sample, and (d) calculating the regression equation of the calibration curve. The process (c) includes a step of calculating an independent component matrix by executing first pre-processing including correcting the observation data, second pre-processing including whitening, and independent component analysis processing in this order. A process suitable for the observation data is selected from a plurality of processes, and is used as the first pre-processing and the second pre-processing.

Abstract: A spectrometer includes a first reflective film, a second reflective film facing the first reflective film with a gap interposed therebetween, a gap change portion that changes the amount of the gap by changing the relative position of the second reflective film with respect to the first reflective film, and a processing unit that outputs optical characteristic data at a predetermined first wavelength interval on the basis of light of a plurality of the wavelengths to be measured which are extracted by the first reflective film and the second reflective film by changing the gap amount using the gap change portion, wherein a full width at half maximum of a spectrum of at least one component of light among the light of the plurality of wavelengths to be measured which are extracted by the first reflective film and the second reflective film is larger than the first wavelength interval.

Abstract: In a method for spectroscopic measurement, a spectroscopic measurement equipment, and a generating method for a transformation matrix, a measured spectrum is converted into a spectrum by making a transformation matrix act on the measured spectrum. The transformation matrix is determined as follows. A known light measured spectrum is linearly projected to a linear space constituted by principal component vectors of the measured spectrum obtained by a reference measurement equipment to thereby convert the known light measured spectrum into a reference known light measured spectrum. The transformation matrix is determined so that an evaluation function, which is defined by a linear combination of a difference between an estimated spectrum obtained by making the transformation matrix act on the reference known light measured spectrum and a known light spectrum, and dispersions of respective components of the transformation matrix, takes an extreme value.

Abstract: A device measures a spectral distribution with respect to each of a plurality of color charts, sets default values to band specification data, and computes a camera output signal based on spectral sensitivity of the multiband camera and spectral feature of light from each of the plurality of charts. The device computes a candidate value of a spectral estimation parameter from the measured spectral distribution of each color chart and the computed camera output signal. The device successively varies the band specification data from the default values to make an evaluation function approach a target value, determines a spectral estimation parameter corresponding to the band specification data when the evaluation function reaches the target value. The evaluation function is defined to correlate the measured spectral distribution of each color chart to a spectral estimation value computed from the candidate value of the spectral estimation parameter and the camera output signal.

Abstract: A method sequentially obtains observation data with respect to a plurality of samples for a test subject and obtains content of a target component contained in each of the plurality of samples. The method subsequently estimates a plurality of independent components, which are separated from the observation data with respect to each of the samples, and calculates a mixing coefficient corresponding to the target component with respect to each of the samples, based on the estimated plurality of independent components. The method then determines a regression equation of a calibration curve, based on the obtained contents of the target component contained in the plurality of samples and the mixing coefficients of the respective samples.

Abstract: An estimation device is configured to estimate a feature value of a specific component contained in a sample and includes: a spectral estimation parameter storage module; a calibration parameter storage module; a multiband image acquirer; an optical spectrum operator configured to compute an optical spectrum from a multiband image using a spectral estimation parameter; and a calibration processor configured to compute the feature value from the optical spectrum using a calibration parameter.

Abstract: A device measures a spectral distribution with respect to each of a plurality of color charts, sets default values to band specification data, and computes a camera output signal based on spectral sensitivity of the multiband camera and spectral feature of light from each of the plurality of charts. The device computes a candidate value of a spectral estimation parameter from the measured spectral distribution of each color chart and the computed camera output signal. The device successively varies the band specification data from the default values to make an evaluation function approach a target value, determines a spectral estimation parameter corresponding to the band specification data when the evaluation function reaches the target value. The evaluation function is defined to correlate the measured spectral distribution of each color chart to a spectral estimation value computed from the candidate value of the spectral estimation parameter and the camera output signal.

Abstract: A server receives simulation condition input from a client computer, and in accordance with the simulation condition input creates display-use data indicating the result of the simulation, and sends the display-use data to the client. The print simulator of the server first converts the image data to ink quantities, and then converts the ink quantities to spectral reflectance of the print. Then, using the spectral reflectance of the print together with the print observation condition and the display device observation condition, there is created display-use data for simulating the appearance of the print under the print observation condition, under the display device observation condition.

Abstract: A printing control device which performs printing control for printing by using color materials of a plurality of types, includes: acquiring unit that acquires a color material set which is a combination of the color materials used for printing; and creation unit that creates a color conversion profile which prescribes conversion rules for converting image data expressed by a first color space into image data expressed by a second color space which differs from the first color space and which is a color space expressed by a color material amount set which is a combination of usage amounts for the respective color materials constituting the color material set.

Abstract: A system is configured to calculate an evaluation index of sample ink amount data from a color difference evaluation index and an image quality evaluation index and create a profile on the basis of a sample with a high rating value. When the image quality evaluation index is predicted, the image quality evaluation index corresponding to any sample ink amount data is estimated based on a profile produced on the basis on actual evaluation. A printer driver is configured to create a plurality of profiles by using different indices in this system and to perform color conversion by using the plurality of profiles. The plurality of profiles are appropriately selected according to the user's needs, printing conditions, and type of printing object image.

Abstract: A second printing control unit is provided. If the setting information is the information of setting for avoiding the use of Cl ink (uncolored ink), the second printing control unit refers to the same color conversion table as is used by a first printing control unit. Thereby the second printing control unit color-converts input image data into image data comprising gradation data corresponding to at least the amounts of colored inks in C, M, Y, R, V, and K consumed. The second printing control unit can carry out such control as to cause a printer (printing device) to use only the C, M, Y, R, V, and K colored ink and print a print image, using the image data.

Abstract: A printing control device includes a texture control unit that acquires texture control data, which is used for controlling the texture of a printing surface of a printing material printed by a printing apparatus, based on texture information data that represents the texture of the printing surface of the printing material.