Seiko Epson Corporation

Jin Hasegawa

Satoru Ono

Toshiya Kondo

Koki Nomura

An information processing device includes: an image data input unit accepting an input of image data; a viewing condition setting acceptance unit accepting a setting of a first viewing condition and a second viewing condition; a color conversion unit converting the image data into first output image data adjusted to an appearance under the first viewing condition, based on a first profile including first spectral information corresponding to the first viewing condition, and converting the image data into second output image data adjusted to an appearance under the second viewing condition, based on a second profile including second spectral information corresponding to the second viewing condition; and a display information generation unit generating display information representing a display screen including the first output image and the second output image, based on the first output image data and the second output image data.

Information processing device, display method, and non-transitory computer-readable storage medium storing display information generation program

A control device includes a memory configured to store variable data including a plurality of page images each including a variable region where an image is variable for each page and a non-variable region including the same image irrespective of the page and a display processing section configured to cause a display device to display a printing preview screen for the variable data. The display processing section causes the display device to display the printing preview screen that displays one or a plurality of row images in which the plurality of page images are arranged in a row in a first direction corresponding to the width direction of a printing medium.

Information processing device, display method, and program

An information processing device includes an information acquisition unit that acquires at least one of attribute information of image data to be image processed and setting information related to the image process on the image data, and a prediction unit that predicts, based on a machine-learned model that accepts input of at least one of the attribute information and the setting information to output a period required for the image process, a period required for the image process on the image data from information acquired by the information acquisition unit.

Information processing device, prediction method, and non-transitory computer-readable storage medium storing program

An information processing device includes: a split printing information setting unit setting split printing information, the split printing information including split position information about a split position in an original image when splitting the original image into a plurality of sub-images and printing the sub-images and overlap area information about an overlap area between the sub-images when pasting together the plurality of sub-images that are printed; and an instruction document preview generation unit generating an instruction document preview based on the split printing information, the instruction document preview being a print preview of a work execution instruction document for pasting together the plurality of sub-images that are printed. The instruction document preview generation unit generates the instruction document preview in such a way that the original image and a work execution image are displayed, the work execution image including a split position image showing the split position in the original image and an overlap area image showing the overlap area.

Information processing device, control method for information processing device, and program

An information processing apparatus storing a machine-learned model that learned, by machine learning, a relationship between a type of a printing medium, an amount of a coloring material on the printing medium per unit area, and an image printed on the printing medium; and estimating, based on a selection information and a imaging information, by using the machine-learned model a limit value indicating a maximum value or a minimum value of an amount of the coloring material to be used in printing on the printing medium by the printing section per unit area; and creating, by using the limit value, a color conversion profile including information regarding mapping between a coordinate value in a color space and an amount of the coloring material.

Apparatus and method for performing color conversions using machine learning

An information processing apparatus configured to store a machine-learned model that learned, by machine learning, a relationship between a type of a printing medium, an amount of a coloring material on the printing medium per unit area, and an image including a gradation image and printed on the printing medium; and estimate, based on a selection information and a imaging information, by using the machine-learned model, a limit value indicating a maximum value or a minimum value of an amount of the coloring material to be used for printing on the printing medium by the printing section per unit area; and create, by using the limit value, a color conversion profile including information regarding mapping between a coordinate value in a color space and an amount of the coloring material.

An information processing apparatus configured to store a machine-learned model that learned, by machine learning, a relationship between a type of a printing medium, an amount of a coloring material on the printing medium per unit area, and an image including a linear image and printed on the printing medium; and estimate, based on a selection information and a imaging information, by using the machine-learned model, a limit value indicating a maximum value or a minimum value of an amount of the coloring material to be used for printing on the printing medium by the printing section per unit area; and create, by using the limit value, a color conversion profile including information regarding mapping between a coordinate value in a color space and an amount of the coloring material.

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Shiojiri, Japan

Jin Hasegawa