Methods and Systems for Detection of a Consumable in a System

• US 20160110624A1
• Filed: 05/22/2014
• Published: 04/21/2016
• Est. Priority Date: 05/24/2013
• Status: Active Grant

• Current Assignee: Life Technologies Corporation (Thermo Fisher Scientific Incorporated)
• Original Assignee: Life Technologies Corporation (Thermo Fisher Scientific Incorporated)
• Inventors: Slettnes, Tor, Chang, Sylvia H., Goyal, Swati, Comstock, David
• Granted Patent: US 9,984,302 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06K 7/1439 including a method step for retrieval of the optical code
• CPC Class Codes: G06V 10/62 relating to a temporal dimension, e.g. time-based feature extraction; Pattern tracking
• CPC Class Codes: G06V 20/635 Overlay text, e.g. embedded captions in a TV program

Abstract

A computer-implemented method for detecting a presence of an object-of-interest in a system is provided. The method includes imaging the first object-of-interest including an identifier, wherein the imaging generates a first set of image data and determining the portion of the image data including the identifier based on a predetermined location. The method further includes dividing the portion of the image data including the identifier into at least two segments Next, the presence of the object-of-interest is determined by determining if intensity values within each segment exceed a presence threshold.

Claims

1. A computer-implemented method for detecting a presence of an object-of-interest in a system, the method comprising:

imaging the first object-of-interest including an identifier, wherein the imaging generates a first set of image data;

determining the portion of the image data including the identifier based on a predetermined location;

dividing the portion of the image data including the identifier into at least two segments; and

determining a presence of the object-of-interest by determining if intensity values within each segment exceed a presence threshold.

2. The computer-implemented method of claim 1, wherein the presence threshold includes a lower threshold and an upper threshold.

3. The computer-implemented method of claim 2, wherein determining a presence of the object-of-interest includes determining peaks in the image data set.

4. The computer-implemented method of claim 3, wherein determining a peak includes determining when the intensity values exceed the upper threshold and are lower than the lower threshold.

5. The computer-implemented method of claim 1, wherein the object-of-interest is determined to be present if more than 4 peaks are determined from each segment.

6. The computer-implemented method of claim 2, wherein the lower threshold is determined by averaging the intensity values in the image data of each segment, and the upper threshold is determined by averaging the brightest ⅔

of intensity values in the image data of each segment.

7. The computer-implemented method of claim 1, further comprising initiating a run on the system after the presence of the object-of-interest is determined.

8. A system for detecting a presence of an object-of-interest in a system, the system comprising:

an optical detector configured to image the first object-of-interest including an identifier, wherein the imaging generates a first set of image data; and

a processor configured to;

determine the portion of the image data including the identifier based on a predetermined location,

divide the portion of the image data including the identifier into at least two segments, and

determine a presence of the object-of-interest by determining if intensity values within each segment exceed a presence threshold.

9. The system of claim 8, wherein the presence threshold includes a lower threshold and an upper threshold.

10. The system of claim 9, wherein determining a presence of the object-of-interest includes determining peaks in the image data set.

11. The system of claim 10, wherein determining a peak includes determining when the intensity values exceed the upper threshold and are lower than the lower threshold.

12. The system of claim 8, wherein the object-of-interest is determined to be present if more than 4 peaks are determined from each segment.

13. The system of claim 9, wherein the lower threshold is determined by averaging the intensity values in the image data of each segment, and the upper threshold is determined by averaging the brightest ⅔

of intensity values in the image data of each segment.

14. The system of claim 8, wherein the processor is further configured to initiate a run on the system after the presence of the object-of-interest is determined.

15. A computer-readable storage medium encoded with processor executable instructions, the instructions including instructions for:

imaging the first object-of-interest including an identifier, wherein the imaging generates a first set of image data;

determining the portion of the image data including the identifier based on a predetermined location;

dividing the portion of the image data including the identifier into at least two segments; and

determining a presence of the object-of-interest by determining if intensity values within each segment exceed a presence threshold.

16. The computer-readable storage medium of claim 15, wherein the presence threshold includes a lower threshold and an upper threshold.

17. The computer-readable storage medium of claim 16, wherein the instructions for determining a presence of the object-of-interest includes instructions for determining peaks in the image data set.

18. The computer-readable storage medium of claim 17, wherein the instructions for determining a peak includes instructions for determining when the intensity values exceed the upper threshold and are lower than the lower threshold.

19. The computer-readable storage medium of claim 15, wherein the object-of-interest is determined to be present if more than 4 peaks are determined from each segment.

20. The computer-readable storage medium of claim 16, wherein the lower threshold is determined by averaging the intensity values in the image data of each segment, and the upper threshold is determined by averaging the brightest ⅔

of intensity values in the image data of each segment.

21. The computer-readable storage medium of claim 15, further comprising instructions for initiating a run on the system after the presence of the object-of-interest is determined.