Sensing and defining an input object

• US 8,269,511 B2
• Filed: 03/26/2010
• Issued: 09/18/2012
• Est. Priority Date: 09/08/2009
• Status: Active Grant

• Current Assignee: Synaptics Incorporated
• Original Assignee: Synaptics Incorporated
• Inventors: Jordan, Joel
• Primary Examiner(s): TANG, MINH NHUT
• Application Number:
  US12/748,001
• Publication Number:
  US 20110057670A1
• Time in Patent Office: 907 Days
• Field of Search: None
• US Class Current: 324/679
• CPC Class Codes: G06F 3/041661 using detection at multiple resolutions, e.g. coarse and fine scanning; using detection within a limited area, e.g. object tracking window
• CPC Class Codes: G06F 3/0443 using a single layer of sensing electrodes

Abstract

A mutual capacitance sensor device comprises a plurality of receiver sensor electrodes, a plurality of transmitter sensor electrodes, and a processing system coupled with the plurality of receiver sensor electrodes and coupled with the plurality of transmitter sensor electrodes. The processing system is configured for acquiring a capacitive image from the pluralities of sensor electrodes. The processing system is also configured for correlating a part of the capacitive image with at least one input object template image to determine both a presence and a type of an input object interacting with the mutual capacitance sensor device.

Claims

1. A mutual capacitance sensor device comprising:

a plurality of receiver sensor electrodes;

a plurality of transmitter sensor electrodes; and

a processing system coupled with said plurality of receiver sensor electrodes and coupled with said plurality of transmitter sensor electrodes, said processing system configured for;

acquiring a capacitive image from said pluralities of sensor electrodes; and

correlating a part of said capacitive image with at least one input object template image to determine both a presence and a type of an input object interacting with said mutual capacitance sensor device.

2. The device of claim 1, wherein said processing system comprises an input object template image storage component in which said at least one input object template image is stored, wherein said at least one input object template image is associated with at least one type of input object.

3. The device of claim 1, wherein said processing system is further configured for:

selecting one of a plurality of input modes based on said determination of said type of said input object.

4. The device of claim 1, wherein said correlating a part of said capacitive image with at least one input object template image to determine both a presence and a type of an input object interacting with said mutual capacitance sensor device comprises:

filtering said capacitive image to determine an input object probability in at least one location in said capacitive image; and

in response to said input object probability exceeding a threshold for a particular location, utilizing said input object template image to determine both said presence and said type of said input object.

5. The device of claim 1, wherein said at least one input object template image represents a hovering human digit capacitive image.

6. The device of claim 1, wherein said at least one input object template image represents a contacting human digit capacitive image.

7. The device of claim 1, wherein said at least one input object template image represents a stylus capacitive image.

8. A method of capacitive input object sensing, said method comprising:

acquiring a capacitive image;

comparing a first part of said capacitive image with a first input object template image, said first input object template image associated with a first type of input object; and

in response to a sufficient correlation between said first part of said capacitive image and said first input object template image, determining a presence of said first type of input object in said capacitive image.

9. The method as recited in claim 8, further comprising:

in response to said presence of said first type of input object being determined, selecting an input mode related to said first type of input object.

10. The method as recited in claim 8, further comprising:

in response to an insufficient correlation existing between said first part of said capacitive image and said first input object template image, comparing said first part of said capacitive image with a second input object template image, said second input object template image associated with a second type of input object;

in response to a sufficient correlation between said capacitive image and said second input object template image, determining a presence of a second type of input object in said capacitive image; and

in response to said presence of said second type of input object being determined, selecting an input mode related to said second type of input object.

11. The method as recited in claim 8, further comprising:

filtering said capacitive image to determine an input object probability in at least one particular location in said capacitive image; and

in response to said input object probability exceeding a threshold for said particular location, establishing a portion of said capacitive image including said particular location as said first part of said capacitive image which is compared with said first input object template image.

12. The method as recited in claim 11, wherein said filtering said capacitive image to determine an input object probability in at least one particular location in said capacitive image comprises:

employing a matched filter on a portion of said capacitive image, said portion including said particular location;

estimating spatially correlated noise with respect to said portion of said capacitive image; and

removing said spatially correlated noise from said portion of said capacitive image to compute said input object probability at said particular location.

13. The method as recited in claim 11, wherein said threshold comprises a threshold based upon a false-detection probability relating to said input object.

14. The method as recited in claim 8, wherein said first input object template image is selected from the group of input object template images consisting of:

a hovering human digit capacitive template image, a contacting human digit capacitive template image, and a stylus capacitive template image.

15. A method of capacitive input object sensing using a mutual capacitance sensor device, said method comprising:

acquiring a capacitive image with a sensor of said mutual capacitance sensor device;

filtering said capacitive image to obtain a filtered capacitive image;

comparing a part of said filtered capacitive image with a first input object template image, said first input object template image associated with a first type of input object; and

in response to a sufficient correlation between said capacitive image and said first input object template, determining a location of said first type of input object with respect to said sensor.

16. The method as recited in claim 15, further comprising:

selecting one of a plurality of input modes for capacitive input object sensing based on determining a presence of said first type of input object.

17. The method as recited in claim 16, wherein said selecting one of a plurality of input modes comprises:

selecting an input mode from the group of input modes consisting of;

a hovering human digit input mode, a contacting human digit input mode, and a stylus input mode.

18. The method as recited in claim 15, wherein said filtering said capacitive image to obtain a filtered capacitive image comprises:

employing a matched filter on said capacitive image.

19. The method as recited in claim 18, wherein said filtering said capacitive image to obtain a filtered capacitive image further comprises:

estimating spatially correlated noise with respect to a portion of said capacitive image; and

removing said spatially correlated noise from said portion of said capacitive image to obtain said filtered capacitive image.

20. The method as recited in claim 15, wherein said filtering said capacitive image to obtain a filtered capacitive image comprises:

filtering said capacitive image to determine an input object probability in at least one particular location in said capacitive image; and

in response to said input object probability exceeding a threshold for said particular location, establishing a portion of said capacitive image including said particular location as said part of said capacitive image which is compared with said first input object template image.