Flow meter

Patent metadata

Field	Value
Publication number	US-10844970-B2
Application number	US-201916585561-A
Country	US
Kind code	B2
Filing date	Sep 27, 2019
Priority date	Dec 21, 2011
Publication date	Nov 24, 2020
Grant date	Nov 24, 2020

Abstract

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 and a valve to regulate the fluid flowing from the drip chamber to a patient. 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 an AND-operation on a pixel on a first side of an axis of the first processed image with a corresponding mirror pixel on a second side of the axis of the first processed image to generate a second processed image.

First claim

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; and
a valve configured to regulate fluid flowing from the drip chamber to a patient, 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 an AND-operation on a pixel on a first side of an axis of the first processed image with a corresponding mirror 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;
performing an edge detection on the image to generate a first processed image, and
performing an AND-operation on a pixel on a first side of an axis of the first processed image with a corresponding mirror 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 , wherein the act of performing the edge detection includes 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 , further comprising applying a blurring function to the image of the drip chamber.

16. The method according to claim 15 , wherein the blurring function is a low pass filter.

17. The method according to claim 15 , wherein the act of applying the blurring function comprises blurring in a vertical direction.

18. The method according to claim 15 , wherein the act of applying the blurring function comprises blurring in a horizontal direction.

19. The method according to claim 15 , wherein the blurring function is a one-dimensional Gaussian Blur function.

20. The method according to claim 15 , wherein the blurring function is a two-dimensional Gaussian Blur function.

Assignees

• Deka Products Lp

Inventors

• Peret Bob D
• Kane Derek G
• Kamen Dean
• Murphy Colin H
• Kerwin John M

Classifications

• G06T7/20

  Analysis of motion (motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51) · CPC title

• A61M5/1411 Primary

  Drip chambers (A61M5/162, A61M5/1689, A61M5/40 take precedence) · CPC title

• G06V10/761

  Proximity, similarity or dissimilarity measures · CPC title

• G06V10/75

  Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries · CPC title

• G06F18/22

  Matching criteria, e.g. proximity measures · CPC title