Baseline update for input object detection

Patent metadata

Field	Value
Publication number	US-11294514-B2
Application number	US-202017008608-A
Country	US
Kind code	B2
Filing date	Aug 31, 2020
Priority date	Oct 30, 2018
Publication date	Apr 5, 2022
Grant date	Apr 5, 2022

Abstract

Baseline update for input object detection includes determining raw measurements from resulting signals acquired for a sensing region, obtaining a masked region of the sensing region based on the raw measurements, and generating a baseline update value using a subset of the raw measurements corresponding to an unmasked region. A baseline value of the masked region is updated using the baseline update value to obtain an updated baseline. A location of an input object is detected using the updated baseline.

First claim

What is claimed is:

1. A processing system comprising:
a processing circuitry configured to:
determine a first plurality of raw measurements from a plurality of resulting signals acquired for a sensing region,
generate a plurality of delta measurements based on the first plurality of raw measurements and baseline values of a previous frame,
add a first mask location to a masked region of the sensing region based on one or more of the delta values in the plurality of delta values being greater than a specified threshold,
generate a baseline update value using a subset of the first plurality of raw measurements corresponding to an unmasked region of the sensing region, the unmasked region and the masked region being concurrently existing locations in the sensing region,
update a baseline value of the masked region using the baseline update value to obtain an updated baseline, and
detect a location of an input object using the updated baseline,
wherein the masked region comprises a plurality of mask locations corresponding to a plurality of possible locations of the input object,
wherein the masked region distinguishes between the plurality of possible locations with the unmasked region determined not to have the input object, and
wherein detecting the location of the input object using the updated baseline comprises detecting the location from the plurality of possible locations.

2. The processing system of claim 1 , wherein the processing circuitry is further configured to:
update at least one baseline value of the unmasked region according to a current baseline and the first plurality of raw measurements to create the updated baseline.

3. The processing system of claim 1 , wherein the processing circuitry is further configured to:
determine a second plurality of raw measurements from the plurality of resulting signals, the plurality of resulting signals spanning a least two sensing frames,
determine, for each corresponding baseline value of at least a subset of baseline values in the updated baseline, a delta value between a raw measurement in the second plurality of raw measurements and the corresponding baseline value to obtain a plurality of delta values, and
detect the location of the input object based on the plurality of delta values satisfying a threshold.

4. The processing system of claim 1 , wherein the processing circuitry is further configured to:
determine whether a transcapacitive image obtained from the first plurality of raw measurements indicates a location of the input object, and
add the location of the input object to the masked region as a second mask location.

5. The processing system of claim 1 , wherein the processing circuitry is further configured to:
compare the first plurality of raw measurements with a second plurality of raw measurements to obtain a comparison result,
the first plurality of raw measurements obtained for a first sensing frame and the second plurality of raw measurements obtained for a second sensing frame, the second sensing frame preceding the first sensing frame, and

add a location to the masked region as a second mask location, based on the comparison result.

6. The processing system of claim 1 , wherein the processing circuitry is further configured to:
obtain a subset of the plurality of raw measurements, the subset of the plurality of raw measurements corresponding to the unmasked region, and
for each pixel in the unmasked region, shift a corresponding baseline value for the pixel by a shift amount determined from a corresponding raw measurement and a current baseline value to obtain an updated baseline value in the updated baseline.

7. The processing system of claim 1 , wherein the processing circuitry is further configured to:
determine a shift amount for each of a plurality of pixels in the unmasked region to obtain a plurality of shift amounts, and
combine the plurality of shift amounts into the baseline update value.

8. The processing system of claim 7 , wherein combining the plurality of shift amounts is averaging the plurality of shift amounts.

9. A method comprising:
determining a first plurality of raw measurements from a plurality of resulting signals acquired for a sensing region;
generating a plurality of delta measurements based on the first plurality of raw measurements and baseline values of a previous frame;
adding a first mask location to a masked region of the sensing region based on one or more of the plurality of delta values being greater than a specified threshold;
generating a baseline update value using a subset of the first plurality of raw measurements corresponding to an unmasked region of the sensing region, the unmasked region and the masked region are concurrently existing locations in the sensing region;
updating a baseline value of the masked region using the baseline update value to obtain an updated baseline; and
detecting a location of an input object using the updated baseline,
wherein the masked region comprises a plurality of mask locations corresponding to a plurality of possible locations of the input object,
wherein the masked region distinguishes between the plurality of possible locations with the unmasked region determined not to have the input object, and
wherein detecting the location of the input object using the updated baseline comprises detecting the location from the plurality of possible locations.

10. The method of claim 9 , further comprising:
determining whether a transcapacitive image obtained from the first plurality of raw measurements indicates a location of the input object, and
adding the location of the input object to the masked region as a second mask location.

11. The method of claim 9 , further comprising:
comparing the first plurality of raw measurements with a second plurality of raw measurements to obtain a comparison result,
the first plurality of raw measurements obtained for a first sensing frame and the second plurality of raw measurements obtained for a second sensing frame, the second sensing frame preceding the first sensing frame, and

adding a second mask location to the masked region based on the comparison result.

12. The method of claim 9 , further comprising:
generating a plurality of delta measurements based on the first plurality of raw measurements and a current baseline, and
adding a second mask location to the masked region based on the plurality of delta measurements.

13. The method of claim 9 , further comprising:
determining a shift amount for each of a plurality of pixels in the unmasked region to obtain a plurality of shift amounts, and
combining the plurality of shift amounts into the baseline update value.

14. An input device comprising:
a plurality of sensor electrodes; and
a processing system operatively connected to the sensor electrodes and configured to:
drive the plurality of sensor electrodes,
acquire, from the plurality of sensor electrodes and based on driving the plurality of sensor electrodes, a plurality of resulting signals of a sensing region,
determine a first plurality of raw measurements from the plurality of resulting signals,
generate a plurality of delta measurements based on the first plurality of raw measurements and baseline values of a previous frame,
add a first mask location to a masked region of the sensing region based on one or more of the delta values in the plurality of delta values being greater than a specified threshold,
generate a baseline update value using a subset of the first plurality of raw measurements corresponding to an unmasked region of the sensing region, the unmasked regi

Assignees

• Synaptics Inc

Inventors

• Kuan Katherine
• Fotopoulos Nickolas

Classifications

• G06F2203/04101

  2.5D-digitiser, i.e. digitiser detecting the X/Y position of the input means, finger or stylus, also when it does not touch, but is proximate to the digitiser's interaction surface and also measures the distance of the input means within a short range in the Z direction, possibly with a separate measurement setup · CPC title

• G06F3/0418 Primary

  for error correction or compensation, e.g. based on parallax, calibration or alignment · CPC title

• G06F2203/04108

  Touchless 2D- digitiser, i.e. digitiser detecting the X/Y position of the input means, finger or stylus, also when it does not touch, but is proximate to the digitiser's interaction surface without distance measurement in the Z direction · CPC title

• G06F2203/04106

  Multi-sensing digitiser, i.e. digitiser using at least two different sensing technologies simultaneously or alternatively, e.g. for detecting pen and finger, for saving power or for improving position detection · CPC title

• G06F3/044 Primary

  by capacitive means · CPC title