Gradual Power Wake-Up Mechanism

• US 20170075700A1
• Filed: 09/08/2016
• Published: 03/16/2017
• Est. Priority Date: 09/11/2015
• Status: Active Application

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Lerner, Arye, D'Souza, Sandeep, Abudi, Yizhaq, Agassy, Meir, Altman, Nathan
• Granted Patent: US 10,261,804 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 1/3206 Monitoring of events, devices or parameters that trigger a change in power modality
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• CPC Class Codes: G06F 3/043 using propagating acoustic waves
• CPC Class Codes: G06F 3/0484 for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text
• CPC Class Codes: G06F 9/4406 Loading of operating system
• CPC Class Codes: G06F 9/4418 Suspend and resume; Hibernate and awake
• CPC Class Codes: G06V 40/1306 non-optical, e.g. ultrasonic or capacitive sensing
• CPC Class Codes: G06V 40/1365 Matching; Classification
• CPC Class Codes: H04M 2250/22 including a touch pad, a touch sensor or a touch detector digitizers for touch screens G06F3/041

Abstract

Apparatuses and methods of a gradual power wake-up mechanism are disclosed. In one embodiment, a method of activating a device based on detection of a fingerprint image may include monitoring a first metric level of a first set of regions of the fingerprint image, determining a second metric level of a second set of regions of the fingerprint image in response to the first metric level exceeding a first threshold, and activating the device based on the second metric level of the second set of regions of the fingerprint image.

Claims

1. A method for use in activating a device based on detection of a fingerprint image, the method comprising:

monitoring a first metric level of a first set of regions of a fingerprint image;

determining a second metric level of a second set of regions of the fingerprint image in response to the first metric level exceeding a first threshold, wherein the second set of regions includes more pixels than the first set of regions; and

activating the device based on the second metric level of the second set of regions of the fingerprint image.

2. The method of claim 1, wherein the first metric level and the second metric level represent at least one of an acoustic energy level, an acoustic loading level, a spatial frequency, a cross-correlation value, or an image quality value.

3. The method of claim 1, wherein monitoring the first metric level of the first set of regions of the fingerprint image comprises:

receiving a first sampled data from the first set of regions of the fingerprint image at a first sampling rate; and

determining the first metric level for indicating an initial prediction of a presence of a finger using the first sampled data.

4. The method of claim 3, further comprising:

monitoring the first metric level of the first set of regions of the fingerprint image in response to the first metric level being less than or equal to the first threshold.

5. The method of claim 1, wherein determining the second metric level of the second set of regions of the fingerprint image comprises:

receiving a second sampled data from the second set of regions of the fingerprint image; and

determining the second metric level for indicating a finer prediction of a presence of a finger using the second sampled data.

6. The method of claim 1, wherein activating the device based on the second metric level of the second set of regions of the fingerprint image comprises:

determining a presence of a finger in response to the second metric level exceeding a second threshold; and

activating the device in response to the presence of the finger.

7. The method of claim 6, further comprising:

monitoring the first metric level of the first set of regions of the fingerprint image in response to the second metric level being less than or equal to the second threshold.

8. The method of claim 3, wherein determining the first metric level of the first set of regions of the fingerprint image comprises:

determining a change in foreground based on a presence of the fingerprint image;

performing a background estimation for the first set of regions of the fingerprint image; and

determining the first metric level of the first set of regions based on differences between the change in foreground and the background estimation for the first set of regions of the fingerprint image.

9. The method of claim 8, wherein determining the change in foreground comprises:

receiving a first sampled foreground data in the first set of sampled data, wherein the first sampled foreground data is collected with an ultrasonic transmitter in an enabled state;

receiving a second sampled foreground data in the first set of sampled data, wherein the second sampled foreground data is collected with the ultrasonic transmitter in a disabled state; and

computing the change in foreground for the first set of regions of the fingerprint image as a difference between the first sampled foreground data and the second sampled foreground data.

10. The method of claim 8, wherein performing the background estimation comprises:

determining an updated acquisition time delay and an updated ultrasonic transmitter frequency in accordance with a variation of a current temperature from a reference temperature from which an initial background estimation and an initial ultrasonic transmitter frequency are determined;

acquiring a background image information based on the updated acquisition time delay and the updated ultrasonic transmitter frequency; and

computing the background estimation using the background image information.

11. The method of claim 10, further comprising at least one of:

reducing background noise based on autocorrelation of the pixels in the first set of regions;

reducing sensor artifacts by removing quiescent values in the first sampled data;

or a combination thereof.

12. A device, comprising:

a sensor having a plurality of sensor pixels configured to sense a fingerprint image;

a memory configured to store the fingerprint image; and

a controller coupled to the sensor and the memory and configured to;

monitor a first metric level of a first set of regions of the fingerprint image;

determine a second metric level of a second set of regions of the fingerprint image in response to the first metric level exceeding a first threshold, wherein the second set of regions includes more pixels than the first set of regions; and

activate the device based on the second metric level of the second set of regions of the fingerprint image.

13. The device of claim 12, wherein the first metric level and the second metric level represent at least one of an acoustic energy level, an acoustic loading level, a spatial frequency, a cross-correlation value, or an image quality value.

14. The device of claim 12, wherein the controller is further configured to:

receive a first sampled data from the first set of regions of the fingerprint image at a first sampling rate; and

determine the first metric level for indicating an initial prediction of a presence of a finger using the first sampled data.

15. The device of claim 14, wherein the controller is further configured to:

monitor the first metric level of the first set of regions of the fingerprint image in response to the first metric level being less than or equal to the first threshold.

16. The device of claim 12, wherein the controller is further configured to:

receive a second sampled data from the second set of regions of the fingerprint image; and

determine the second metric level for indicating a finer prediction of a presence of a finger using the second sampled data.

17. The device of claim 12, wherein the controller is further configured to:

determine a presence of a finger in response to the second metric level exceeding a second threshold; and

activate the device in response to the presence of the finger.

18. The device of claim 17, wherein the controller is further configured to:

monitor the first metric level of the first set of regions of the fingerprint image in response to the second metric level being less than or equal to the second threshold.

19. The device of claim 14, wherein the controller is further configured to:

determine a change in foreground based on a presence of the fingerprint image;

perform a background estimation for the first set of regions of the fingerprint image; and

determine the first metric level of the first set of regions based on differences between the change in foreground and the background estimation for the first set of regions of the fingerprint image.

20. The device of claim 19, wherein the controller is further configured to:

receive a first sampled foreground data in the first set of sampled data, wherein the first sampled foreground data is collected with an ultrasonic transmitter in an enabled state;

receive a second sampled foreground data in the first set of sampled data, wherein the second sampled foreground data is collected with the ultrasonic transmitter in a disabled state; and

compute the change in foreground for the first set of regions of the fingerprint image as a difference between the first sampled foreground data and the second sampled foreground data.

21. The device of claim 19, wherein the controller is further configured to:

determine an updated acquisition time delay and an updated ultrasonic transmitter frequency in accordance with a variation of a current temperature from a reference temperature from which an initial background estimation and an initial ultrasonic transmitter frequency are determined;

acquire a background image information based on the updated acquisition time delay and the updated ultrasonic transmitter frequency; and

compute the background estimation using the background image information.

22. The device of claim 21, wherein the controller is further configured to perform at least one of:

reduce background noise based on autocorrelation of the pixels in the first set of regions;

reduce sensor artifacts by removing quiescent values in the first sampled data;

or a combination thereof.

23. A non-transitory medium storing instructions for execution by one or more processors of a device, the instructions comprising:

instructions for monitoring a first metric level of a first set of regions of a fingerprint image;

instructions for determining a second metric level of a second set of regions of the fingerprint image in response to the first metric level exceeding a first threshold, wherein the second set of regions includes more pixels than the first set of regions; and

instructions for activating the device based on the second metric level of the second set of regions of the fingerprint image.

24. The non-transitory medium of claim 23, wherein the instructions for monitoring the first metric level of the first set of regions of the fingerprint image comprise:

instructions for receiving a first sampled data from the first set of regions of the fingerprint image at a first sampling rate; and

instructions for determining the first metric level for indicating an initial prediction of a presence of a finger using the first sampled data.

25. The non-transitory medium of claim 23, wherein the instructions for determining the second metric level of the second set of regions of the fingerprint image comprise:

instructions for receiving a second sampled data from the second set of regions of the fingerprint image; and

instructions for determining the second metric level for indicating a finer prediction of a presence of a finger using the second sampled data.

26. The non-transitory medium of claim 23, wherein the instructions for activating the device based on the second metric level of the second set of regions of the fingerprint image comprise:

instructions for determining a presence of a finger in response to the second metric level exceeding a second threshold; and

instructions for activating the device in response to the presence of the finger.

27. The non-transitory medium of claim 24, wherein the instructions for determining the first metric level of the first set of regions of the fingerprint image comprise:

instructions for determining a change in foreground based on a presence of the fingerprint image;

instructions for performing a background estimation for the first set of regions of the fingerprint image; and

instructions for determining the first metric level of the first set of regions based on differences between the change in foreground and the background estimation for the first set of regions of the fingerprint image.

28. A device, comprising:

means for use in sensing a fingerprint image using a plurality of sensor pixels;

means for use in storing the fingerprint image;

means for monitoring a first metric level of a first set of regions of the fingerprint image;

means for determining a second metric level of a second set of regions of the fingerprint image in response to the first metric level exceeding a first threshold, wherein the second set of regions includes more pixels than the first set of regions; and

means for activating the device based on the second metric level of the second set of regions of the fingerprint image.

29. The device of claim 28, wherein the means for monitoring the first metric level of the first set of regions of the fingerprint image comprises:

means for receiving a first sampled data from the first set of regions of the fingerprint image at a first sampling rate; and

means for determining the first metric level for indicating an initial prediction of a presence of a finger using the first sampled data.

30. The device of claim 28, wherein the means for determining the second metric level of the second set of regions of the fingerprint image comprises:

means for receiving a second sampled data from the second set of regions of the fingerprint image; and

means for determining the second metric level for indicating a finer prediction of a presence of a finger using the second sampled data.