Seiko Epson Corporation

Mitsuhiro Yamashita

Yuko Yamamoto

Takahiro Kamada

Takuya Ono

Kenji Fukasawa

Hirofumi Sakai

Seishin Yoshida

Ryoki Watanabe

Kenji Matsuzaka

Takumi Shimomukai

Satoru Ono

Katsuyuki Tanaka

Masayuki Seko

Naoki Hagihara

Hirohisa Ozawa

Shotaro Matsuda

The print medium identification method includes (a) a step of obtaining first physical property information about a print medium, (b) a step of obtaining second physical property information which is different from the first physical property information about the print medium, (c) a step of obtaining first discrimination information for discriminating a type of print medium by inputting the first physical property information to a first discriminator, (d) a step of obtaining second discrimination information for discriminating the type of print medium by inputting second physical property information to a second discriminator, and (e) a step of identifying the type of print medium by using the first discrimination information and the second discrimination information.

Print medium identification method and print medium identification system

A print image is acquired as first image data represented in a first color space used for forming an image on a first print medium. Second image data is acquired by performing, on the first image data, conversion into representation in a profile connection space using a first conversion table and white point conversion using the information on appearance in a redetermined observation environment, of a base color section where an image is not formed on the first print medium. The second image data is converted by using a second conversion table into converted image data represented in a second color space used for forming an image on a second print medium and an image corresponding to the print image is formed on the second print medium by using the converted image data.

Image processing device and image processing program

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.

Defect discrimination apparatus for printed images and defect discrimination method

An image processing device converts image data, which is data of an image expressed in a first color space, into an expression in a second color space used in rendering by using a color conversion profile prepared in advance, generates a converted image data, and generates a rendering image corresponding to the appearance of the printed-on print medium in a virtual space by performing physical based rendering of the printed-on print medium on which the image has been printed, using the converted image date and parameters necessary for performing physical based rendering of the print medium as a 3D object.

Image processing device for previewing image to be printed on 3D object

An image processing device includes an image data acquisition section configured to acquire image data of an image to be printed on a print medium; a parameter acquisition section configured to acquire parameters for performing physical based rendering of the print medium on which the image is to be printed as a 3D object, the parameters including a normal line map representing a normal line direction of an irregularities surface of the print medium related to a reflection direction of light incident on the print medium; a correction section configured to correct strength of an application effect of the normal line map corresponded with the 3D object; and a rendering execution section for generating a rendering image representing the print medium on which the image is printed by executing the physical based rendering using the image data and the parameters.

Image processing device, printing system, and non-transitory computer-readable storage medium storing image processing program that render three dimensional (3D) object

An image processing device includes: an image data acquisition unit that acquires image data; a print condition acquisition unit that acquires a print condition including a type of a print medium on which an image is printed; a parameter acquisition unit that acquires a texture parameter indicating a texture of the print medium; a color conversion unit that performs color conversion corresponding to the print condition, on the image data; and a rendering unit that executes rendering, causing the image data on which the color conversion is performed, to correspond to at least one of a front face and a back face of a 3D object representing a shape of the print medium, and causing the texture parameter to correspond to the front face and the back face of the 3D object, and thus generates a rendered image representing the print medium with the image printed thereon.

Image processing device, printing system, and non-transitory computer-readable storage medium storing image processing program

A printing method includes: a color space conversion step; a gradation determination step of determining whether a pixel group forms a gradation; and a gradation region ink amount calculation step of calculating an ink amount of the pixel group determined to form the gradation. The gradation region ink amount calculation step includes an array information acquisition step of acquiring whether pixel values are arranged linearly, in a planar manner, or in a polyhedron manner in a uniform color space, a grating color value calculation step of determining a grating color value which is a color value of a grating point in the array, a grating ink amount calculation step of calculating, using the determined grating color value, a grating ink amount which is an ink amount of the grating point in the array, and an interpolation calculation step of calculating an ink amount of the pixel group determined to form the gradation by interpolation using the calculated grating ink amount.

Printing method including gradation region ink amount calculation step

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.

Image analyzer determines in-use ink information using image data according to preset conditions and acquires prespecified image quality information when image is printed

For a plurality of kinds of printing media, spectral information is produced from results of printing of at least five points in paper white of the printing media, black, and three primary colors of coloring and printing materials, and a learned model is generated in advance by machine learning that uses the spectral information as learning data. An identification section that identifies the kinds of the printing media by using the learned model is provided. The kinds of the printing media are identified by applying the spectral information produced from the results of printing of at least five points on a printing target medium on which printing is to be performed to the learned model, and the printing target medium is processed in accordance with the identified kind of the printing target medium. In the case of a new unlearned printing medium, transfer learning is performed to learn the printing medium, and the model is updated.

Printing medium processing system and printing medium processing method

For a plurality of types of print media, a pre-trained model is prepared, the pre-trained model being generated by machine learning based on spectroscopic information of an unprinted area on the print medium and an identifier indicating the type of the print medium and using the identifier as a trainer. The spectroscopic information of the unprinted area on the print medium to print on is acquired. The acquired spectroscopic information is applied to the pre-trained model. Using a result thereof, auxiliary information about the type of the print medium is outputted. A specification of the type of the print medium using the outputted auxiliary information is accepted. When the type of the print medium is thus specified, printing is performed using a print condition suitable for the print medium.

Printing system, print medium specifying method, and medium information providing device

A printing condition setting method is a printing condition setting method of setting printing conditions in a printing apparatus, including a learning step of performing machine learning by using ink physical characteristics and ink type information, a similarity score calculation step of calculating a similarity score indicating a similarity of a use ink used for printing in the printing apparatus with respect to a learned ink learned in the learning step, and a printing condition setting step of setting the printing conditions according to the use ink based on the similarity score.

Printing condition setting method, printing condition setting system

A method of creating teacher data used for creating a color prediction model that predicts a spectral reflectance of a printed matter printed using an ink amount set from the ink amount set that is a combination of ink amounts of inks used for printing, includes, in an ink amount space in which a plurality of lattice points are disposed, selecting an ink amount set from an ink amount set associated with each lattice point, according to a predetermined selection rule, acquiring a spectral reflectance of a color chart printed on a printing medium using the selected ink amount set, and setting the teacher data using the selected ink amount set as an input value and the acquired spectral reflectance as an output value.

Method of creating teacher data, color prediction model creation apparatus, and method of creating color prediction model

A device link profile adjustment method of a computer carrying out a process of adjusting a device link table in a device link profile expressing a correspondence relationship between a first coordinate value of a first device-dependent color space and a second coordinate value of a second device-dependent color space, the method including: accepting an adjustment target at an adjustment point, using a coordinate in a profile connection space as a reference; and adjusting the device link table based on the adjustment target and a color conversion table including a device-independent coordinate value of the profile connection space of an original profile used to create the device link table.

Device link profile adjustment method, device link profile adjustment apparatus, and device link profile creation method

A color conversion information generation device generates one or a plurality of intermediate points located on a first line segment connecting a first coordinate value representing a first color in a first color space and a second coordinate value representing a second color, in such a way that a number of intermediate points included in each of a plurality of reference spaces corresponding to a plurality of reference points is one or fewer. The color conversion information generation device generates modified conversion information in such a way that, when a coordinate value on the first line segment is converted into a coordinate value in a second color space by the modified conversion information, the coordinate value resulting from the conversion reflects one of a first adjustment value, a second adjustment value, and a third adjustment value. The color conversion information generation device generates color conversion information for converting a fourth coordinate value on the first line segment generated based on an operation by a user, into a coordinate value in the second color space, based on the modified conversion information.

Method for generating color conversion information, color conversion information generation program, and color conversion information generation device

A color conversion information generation apparatus converts a first coordinate value into a second coordinate value in a second color space by using first conversion information, acquires a colorimetric coordinate value in a first color space indicating a colorimetric result of an image output by a first output apparatus according to the second coordinate value, converts the second coordinate value into a third coordinate value by using second conversion information, determines a target coordinate value indicating a target color in the first color space based on the third coordinate value and a difference between the first coordinate value and the colorimetric coordinate value, retrieves a fourth coordinate value satisfying a condition that a color difference between a fifth coordinate value in the first color space obtained by converting a fourth coordinate value in the second color space by using the second conversion information and the target coordinate value is smaller than a color difference between the third coordinate value and the target coordinate value, and generates color conversion information used to convert the first coordinate value or a name of a color into a coordinate value in the second color space based on the first coordinate value and the fourth coordinate value satisfying the condition.

Color conversion information generation method, non-transitory computer-readable storage medium storing color conversion information generation program, and color conversion information generation apparatus

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Nagano, Japan

Mitsuhiro Yamashita