IP Library › Granted Patent US 12,533,902
Granted Patent B2
US 12,533,902 · App. 17/972,325 · Granted Jan 27, 2026

Methods and system for adjusting formulation of pigments and performing dye sublimation printing

Inventors: Jeffrey Humenick (Bloomsburg, PA); Jym Kauffman (Bloomsburg, PA); Rebecca Gallup (Bloomsburg, PA)
Assignee: SEKISUI KYDEX, LLC
B41M5/382B41M5/0256B41M5/035G01N33/32G06V10/82G06V10/993
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Quick Facts
Patent No.
US 12,533,902
App. No.
17/972,325
Granted
Jan 27, 2026
Kind
B2
Abstract

Methods and systems for adjusting formulation of pigments for dye sublimation are disclosed. In one embodiment, the method includes receiving, by a processor, a selection of the substrate and the image to be dye sublimated into the substrate. The method also includes determining, by the processor, an amount of each pigment of sublimation ink to be used to print the image on a sheet based on a characteristic of the substrate. The method further includes printing, by a dye sublimation apparatus, the image on the sheet using the amount of each pigment of sublimation ink and infusing, by the dye sublimation apparatus, the image from the sheet into the substrate.

Claims (52)

1 . A computer-implemented method for printing an image to be infused into a substrate through dye sublimation, the method comprising:

receiving, by a processor, a selection of the substrate and the image to be dye sublimated into the substrate;

determining, by the processor, an amount of each pigment of sublimation ink to be used to print the image on a sheet based on at least one of a characteristic of the substrate and the image, wherein the determination includes:

providing the at least one characteristic of the substrate and the image to a database; and

receiving from the database the amount of each pigment of sublimation ink;

printing, by a dye sublimation apparatus, the image on the sheet using the amount of each pigment of sublimation ink; and

infusing, by the dye sublimation apparatus, the image from the sheet into the substrate.

2 . The method of claim 1 , wherein the at least one characteristic of the substrate and the image includes at least one of a color and a material of the substrate.

3 . The method of claim 1 , further comprising:

collecting, by the processor, a plurality of images that were infused into a plurality of substrates;

creating, by the processor, a training set comprising the plurality of images, the amount of each pigment of sublimation ink that was used for the plurality of images, and characteristics of the plurality of substrates that were infused with the plurality of images; and

training, by the processor, a neural network using the training set,

wherein determining the amount of each pigment includes inputting, by the processor, the selection of the substrate and the image into the neural network.

4 . The method of claim 3 , wherein each of the plurality of images includes at least one of a single pixel of an image, a portion of an image, or an entirety of an image.

5 . The method of claim 3 , further comprising, outputting, by the neural network, the amount of each pigment of sublimation ink within a threshold.

6 . The method of claim 3 , wherein the neural network is configured to output a predicted amount of each pigment of sublimation ink within a threshold for the substrate.

7 . The method of claim 3 , further comprising populating a database connected to the processor with the training set and a predicted amount of each pigment of sublimation ink within a threshold for the substrate output by the neural network.

8 . The method of claim 1 , wherein the database includes a plurality of entries of the amount of each pigment according to the substrates.

9 . The method of claim 1 , wherein the substrate is a first substrate, the method further comprising:

collecting, by the processor, a plurality of images that were infused into a plurality of substrates, the amount of each pigment of sublimation ink that was used for the plurality of images, and characteristics of the substrates that were used for the plurality of images;

creating, by the processor, a plurality of training sets, wherein each of the plurality of training sets is associated with one of the plurality of substrates; and

training, by the processor, a neural networks for each of the plurality of training sets, wherein the neural networks are configured to output a predicted amount of each pigment of sublimation ink within a threshold for the associated one of the plurality of substrates;

wherein determining the amount of each pigment includes selecting the predicted amount from the neural network associated with the first substrate.

10 . A system for printing an image to be infused into a substrate through dye sublimation, comprising:

a processor configured to:

receive the substrate and the image to be dye sublimated into the substrate; and

determine an amount of each pigment of sublimation ink based on the image and the substrate, wherein determine the amount of each pigment of sublimation ink includes:

input at least one characteristic of the substrate and the image into a neural network; and

receive the amount of each pigment of sublimation ink from the neural network;

a printer configured to print the image on a sheet using the amount of each pigment of sublimation ink; and

a dye sublimation apparatus configured to dye sublimate the image into the substrate.

11 . The system of claim 10 , wherein the at least one characteristic of the substrate includes at least one of a color and material of the substrate.

12 . The system of claim 10 , wherein the processor is further configured to:

collect a plurality of images that were infused into a plurality of substrates;

create a training set comprising the plurality of images, the amount of each pigment of sublimation ink that was used for the plurality of images, and characteristics of the plurality of substrates that were infused with the plurality of images; and

train the neural network using the training set.

13 . The system of claim 12 , wherein each of the plurality of images includes at least one of a single pixel of an image, a portion of an image, or an entirety of an image.

14 . The system of claim 12 , wherein the neural network is configured to output the amount of each sublimation ink within a threshold.

15 . The system of claim 10 , wherein determine the amount of each pigment of sublimation ink includes:

select, as the neural network, a neural network associated with the substrate from a plurality of neural networks corresponding to a plurality of substrates;

input the image into the selected neural network; and

receive the amount of each pigment of sublimation ink from the selected neural network.

16 . A system for printing an image to be infused into a substrate through dye sublimation, comprising;

a processor configured to:

receive the substrate and the image to be dye sublimated into the substrate; and

determine an amount of each pigment of sublimation ink based on the image and the substrate, wherein determine the amount of each pigment of sublimation ink includes:

provide at least one characteristic of the substrate and the image to a database; and

receive from the database the amount of each pigment of sublimation ink;

a printer configured to print the image on a sheet using the amount of each pigment of sublimation ink; and

a dye sublimation apparatus configured to dye sublimate the image into the substrate.

17 . The system of claim 16 , wherein the database includes a plurality of entries of the amount of each pigment according to the substrate.

18 . The system of claim 17 , wherein the database is populated with a plurality of entries of the amount of each pigment according to the substrate by a neural network trained using a training set comprising a plurality of images, an amount of each pigment of sublimation ink that was used for the plurality of images, and characteristics of a plurality of substrates that were infused with the plurality of images.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 24, 2022
From: HUMENICK, JEFFREY; KAUFFMAN, JYM; GALLUP, REBECCA
To: SEKISUI KYDEX, LLC
Reel/Frame 061518/0991 →
Continuity (2)
Provisional Application 63272117 · Oct 26, 2021
Related Publication 20230128030A1 · Apr 27, 2023
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