Systems and methods for classifying images of an imprinted film
US-2021042906-A1 · Feb 11, 2021 · US
US12254408B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12254408-B2 |
| Application number | US-202017756393-A |
| Country | US |
| Kind code | B2 |
| Filing date | Dec 15, 2020 |
| Priority date | Dec 16, 2019 |
| Publication date | Mar 18, 2025 |
| Grant date | Mar 18, 2025 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
A method of producing an image of at least one rock cutting. The method can include forming or obtaining a substrate having a patterned top surface. The method can also include using the patterned top surface of the substrate to support at least one rock cutting, controlling an image acquisition system to acquire at least one image of the rock cutting for storage and subsequent image processing.
Opening claim text (preview).
What is claimed is: 1. A method for automated classification of rock cuttings, comprising: forming a substrate having a patterned top surface; while using the patterned top surface of the substrate to support a rock cutting, producing, by an image acquisition system, a sequence of images of the rock cutting using focal plane stacking; processing, by one or more computers, the sequence of images by aligning and merging the images to generate a sharpened image of the rock cutting; inputting as training data, by the one or more computers, the sharpened image of the rock cutting into an automated texture-based deep learning classifier of rock cuttings; and classifying a rock cutting using the automated texture-based deep learning classifier that has been trained using the sharpened image. 2. A method according to claim 1 , wherein: the image acquisition system comprises a camera with a fixed or variable focus lens and a light source. 3. A method according to claim 1 , further comprising: controlling the image acquisition system to acquire the sequence of images of the rock cutting, each at different focus settings corresponding to different height levels across a height of the rock cutting, wherein at least one of the focus settings corresponds to the plane of the patterned top surface of the substrate. 4. A method according to claim 3 , wherein: the focus setting corresponding to the plane of the patterned top surface of the substrate focuses the image acquisition system on patterns formed in the patterned substrate. 5. A method according to claim 3 , wherein: the focus setting corresponding to the plane of the patterned top surface of the substrate is determined manually or by automatic methods. 6. A method according to claim 3 , further comprising: registering or storing in electronic form the focus setting corresponding to the plane of the patterned top surface of the substrate for access and use in imaging at least one additional sample of rock cuttings. 7. A method according to claim 1 , wherein: the patterned top surface of the substrate is formed by laser cutting, or by printing or other deposition of nanoparticles. 8. A method according to claim 1 , wherein: the patterned top surface of the substrate is defined by a dithering algorithm. 9. A method according to claim 1 , wherein: the patterned top surface provides a blue background for the rock cutting. 10. A method according to claim 1 , which is configured to produce an image of a plurality or mixture of rock cuttings. 11. A method according to claim 8 , wherein: the dithering algorithm is a Stucki dithering, a Floyd-Steinberg dithering, or a Jarvis dithering. 12. A system for producing an image of at least one rock cutting, comprising: a substrate having a patterned top surface and configured to support a rock cutting; and an image acquisition system configured to acquire a sequence of images of the rock cutting using focal plane stacking while the rock cutting is supported on the patterned top surface of the substrate.
Convolutional networks [CNN, ConvNet] · CPC title
Earth observation · CPC title
Analysis of geometric attributes · CPC title
Earth materials (G01N33/42 takes precedence) · CPC title
by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.