Craniofacial External Distraction Apparatus
US-2015238228-A1 · Aug 27, 2015 · US
US11793928B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11793928-B2 |
| Application number | US-202217749672-A |
| Country | US |
| Kind code | B2 |
| Filing date | May 20, 2022 |
| Priority date | Dec 21, 2011 |
| Publication date | Oct 24, 2023 |
| Grant date | Oct 24, 2023 |
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 system for regulating fluid flow having a processor configured to reduce image noise is provided. The system includes an image sensor to capture an image of the drip chamber. The processor captures the image of the drip chamber using the image sensor, performs an edge detection on the image to generate a first processed image, and performs a Boolean-operation on a pixel on a first side of an axis of the first processed image with a corresponding pixel on a second side of the axis of the first processed image to generate a second processed image.
Opening claim text (preview).
What is claimed is: 1. A system for regulating fluid flow having a processor configured to reduce image noise, the system comprising: an image sensor configured to capture an image of a drip chamber, wherein the processor is configured to: capture the image of the drip chamber using the image sensor, perform an edge detection on the image to generate a first processed image, and perform a Boolean-operation on a pixel on a first side of an axis of the first processed image with a corresponding pixel on a second side of the axis of the first processed image to generate a second processed image. 2. The system according to claim 1 , wherein the edge detection is performed using a canny edge detection. 3. The system according to claim 1 , wherein the processor is configured to match a template to the image. 4. The system of claim 3 , wherein the template includes at least a partial image of a drop of the fluid forming within the drip chamber. 5. The system of claim 1 , wherein the processor is configured to apply a blurring function to the image captured by the image sensor of the drip chamber. 6. The system according to claim 5 , wherein the blurring function is a low pass filter. 7. The system according to claim 5 , wherein the blurring function is configured to blur in a vertical direction. 8. The system according to claim 5 , wherein the blurring function is configured to blur in a horizontal direction. 9. The system according to claim 5 , wherein the blurring function is a one-dimensional Gaussian Blur function. 10. The system according to claim 5 , wherein the blurring function is a two-dimensional Gaussian Blur function. 11. A method for reducing image noise, the method comprising: capturing an image of a drip chamber; applying a blurring function to the image of the drip chamber; and performing a Boolean-operation on a pixel on a first side of an axis of a first processed image with a corresponding pixel on a second side of the axis of the first processed image to generate a second processed image. 12. The method according to claim 11 , further comprising performing a canny edge detection. 13. The method according to claim 11 , further comprising matching a template to the image. 14. The method according to claim 13 , wherein the template includes at least a partial image of a drop of the fluid forming within the drip chamber. 15. The method according to claim 11 , wherein the blurring function is a low pass filter. 16. The method according to claim 11 , wherein the act of applying the blurring function comprises blurring in a vertical direction. 17. The method according to claim 11 , wherein the act of applying the blurring function comprises blurring in a horizontal direction. 18. The method according to claim 11 , wherein the blurring function is a one-dimensional Gaussian Blur function. 19. The method according to claim 11 , wherein the blurring function is a two-dimensional Gaussian Blur function.
Related publications grouped by family.
Answers are generated from the same data shown on this page.