Abstract:
An print medium specification method includes (a) step for acquiring first physical property information related to the print medium; (b) step for acquiring second physical property information different from the first physical property information related to the print medium; (c) step for acquiring a discrimination information for discriminating the type of the print medium by inputting the first physical property information to a discrimination function configured as a learned machine learning model; and (d) step for specify a type of the print medium using the discrimination information and the second physical property information not used for machine learning.
Abstract:
Provided is an image processing device coupled to a printing device that performs printing on a medium by ejecting ink having a plurality of colors, and configured to convert image data into ink amount data. The image processing device includes: an input unit configured to input a search condition; an acquisition unit configured to acquire a plurality of search values based on the search condition input by the input unit; a table storage unit storing a plurality of image conversion tables for converting the image data into the ink amount data; and a search unit configured to search the plurality of image conversion tables for a target image conversion table based on the plurality of search values acquired by the acquisition unit.
Abstract:
A printing apparatus including: a first nozzle group including a first and third nozzles which ejects a first liquid; and a second nozzle group including a second nozzle which ejects a second liquid, in which, when an ejection state of the liquid ejected from the one nozzle which belongs to the first nozzle group is abnormal, complementation is performed using complementation modes of a first complementation mode that increases the amount of a liquid to be ejected from the first nozzle instead of allowing the one nozzle to eject the liquid, a second complementation mode that increases the amount of the liquid to be ejected from the second nozzle instead of allowing the one nozzle to eject the liquid, and a third complementation mode that increases the amount of the liquid to be ejected from the third nozzle instead of allowing the liquid to be ejected from the one nozzle.
Abstract:
An image processing device includes a shielding degree calculation section that calculates a shielding degree of a printed layer, and a rendering section. The rendering section is configured to generate at least one of the front surface view, in which the printed object is observed from the front surface side, and the back surface view, in which the printed object is observed from the back surface side, by mapping an image data, which is color converted, to a 3D object and by performing rendering using the shielding degree of the printed layer.
Abstract:
An image analyzer includes an in-use ink information determination section that determines an ink type to be used for printing and an ink quantity to be used for printing for the ink type as in-use ink information by using image data in accordance with conditions set in advance, a printed image quality information acquisition section that acquires at least one item of printed image quality information on image quality specified in advance and provided when the image data is printed by using the determined in-use ink information, and a display section that displays at least one of the in-use ink information and the printed image quality information.
Abstract:
Prepare a learning model that has been trained to output similarity for each defect species by machine learning using a teacher image that is an image containing a defect occurring during printing and that is associated with a defect species in advance. Then, a target image is prepared for inspection by acquiring an image of printed matter that has been printed. By using the learning model with respect to this target image, the similarity of the defect present in the target image to a known defect species is acquired, and this similarity is used to discriminate the defect present in the target image as at least one of the known defect species. When updating the learning model based on this discrimination result, the learning model is made to perform machine learning for a defect species that is different from the discriminated defect species or that is associated with an unknown defect.
Abstract:
A printing system includes a terminal device, a plurality of printers, a first server, and a second server. The first server calculates a round-trip accuracy of each printer using a color conversion profile supplied from the second server with respect to target color information included in a printing command provided from the terminal device, and selects one or more printers among the plurality of printers according to the round-trip accuracy to cause the printers to execute printing.
Abstract:
A color value prediction system includes a color-value predicting section configured to receive an input of information representing ink amounts of a first apparatus and output spectral reflectance, a receiving section configured to receive an input of information representing a designated color gamut, a preparing section configured to prepare first teacher information representing a plurality of sets of combinations of ink amounts of the first apparatus and second teacher information, which is a plurality of sets of spectral reflectance respectively associated with the plurality of sets of combinations of ink amounts of the first teacher information, and a generating section configured to generate the color-value predicting section with machine learning in which the first teacher information serving as an input value and the second teacher information serving as an output value are used as teacher data. The first teacher information includes designated teacher information representing a combination of ink amounts of the first apparatus representing a color included in the designated color gamut.
Abstract:
A liquid ejecting apparatus including: a first nozzle group including first nozzles which eject a liquid with a first color absorbing light having a predetermined wavelength, a second nozzle group including second nozzles which eject a liquid with a second color absorbing light having a predetermined wavelength, and Q (Q is a natural number satisfying “2≦Q”) nozzle groups including nozzles which eject a liquid other than the liquid having the first color and the liquid having the second color; the first nozzle group is provided in a first area, the second nozzle group is provided in a second area, and the Q nozzle groups are not provided between the first area and the second area but provided on the upstream side or the downstream side of the first area and the second area.
Abstract:
It is an object of the present invention to provide an ink set which makes it possible to obtain recorded images that have a broad color reproduction range and a high saturation, as well as glossiness without conspicuous graininess caused by dot expression, and which in particular makes it possible to achieve an extreme suppression of graininess caused by dot expression in cases where the ink set is used on media that have a coating layer, and to obtain recorded images with extremely superior coloring characteristics in cases where the ink set is used on ordinary paper. The present invention provides an ink set comprising at least a yellow ink (Y), magenta ink (M), cyan ink (C) and red ink (R), wherein the L* values in the CIE-stipulated Lab display system of aqueous solutions of the respective inks diluted 1000 times by weight are in the following ranges: (Y): at least 89 but no more than 94, (M): at least 76 but no more than 93, (C): at least 74 and no more than 87, (R): at least 55 and no more than 74.