Sensing and defining an input object

• US 9,098,139 B2
• Filed: 08/17/2012
• Issued: 08/04/2015
• 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 N
• Application Number:
  US13/588,909
• Publication Number:
  US 20120310572A1
• Time in Patent Office: 1,082 Days
• Field of Search: None
• US Class Current: 1/1
• 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

An input device comprises a display, a plurality of sensor electrodes, and a processing system. The plurality of sensor electrodes is configured to detect an input object in a sensing region of the input device. The sensing region overlaps the display. The processing system is coupled with the plurality of sensor electrodes. The processing system is configured for: acquiring a capacitive image from the plurality of sensor electrodes; and correlating a part of the capacitive image with at least one input object template image to determine a type of an input object interacting with the input device.

Claims

1. An input device comprising:

a display;

a plurality of sensor electrodes configured to detect an input object in a sensing region of said input device, wherein said sensing region overlaps said display; and

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

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

correlating a part of said capacitive image with at least one input object template image to determine a type of an input object interacting with said input device.

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

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

5. The input device of claim 4, wherein said processing system is further configured for:

establishing a portion of said capacitive image, including said at least one particular location, as a first part of said sensing region in response to said input object presence probability exceeding a threshold.

6. The input device of claim 4, wherein said filtering said capacitive image to determine an input object presence probability in at least one particular location in said capacitive image comprises:

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

removing said spatially correlated noise from said capacitive image.

7. The input device of claim 1, wherein said correlating a part of said capacitive image with at least one input object template image to determine a type of an input object interacting with said input device comprises:

in response to an input object presence probability exceeding a threshold in at least one particular location in said capacitive image, utilizing said input object template image to determine said type of said input object.

8. The input device of claim 1, wherein said at least one input object template image is selected from the group of input object template images consisting of:

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

9. 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;

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; and

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

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

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

in response to a sufficient correlation between said second part of said capacitive image and one of said first and second input object template images;

determining a type of input object in said capacitive image; and

selecting an input mode related to said type of input object.

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

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

in response to said input object presence 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.

12. The method as recited in claim 11, wherein said filtering said capacitive image to determine an input object presence 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 presence 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 9, wherein said first and second input object templates image are 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 processing system for a capacitive input device object sensing using a mutual capacitance sensor device, said processing system comprising:

memory configured to store a plurality of input object template images, wherein the processing system is configured to;

acquire a capacitive image with a sensor of said capacitive input device;

compare a 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 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 processing system of claim 15, wherein said processing system is further configured to:

select 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.

17. The processing system of claim 15, wherein said processing system is further configured to:

filter said capacitive image to obtain a filtered capacitive image, wherein the processing system compares said first input object template image with a part of said filtered capacitive image.

18. The processing system of claim 17, wherein said processing system being configured to filter said capacitive image to obtain a filtered capacitive image comprises:

said processing system being configured to employ a matched filter on said capacitive image to obtain said filtered capacitive image.

19. The processing system of claim 17, wherein said processing system being configured to filter said capacitive image to obtain a filtered capacitive image comprises:

said processing system being configured to;

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

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

20. The processing system of claim 17, wherein said processing system being configured to filter said capacitive image to obtain a filtered capacitive image comprises:

said processing system being configured to;

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

in response to said input object presence probability exceeding a threshold for said particular location, establish 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.