Automatic adjustment processing for sensor devices

• US 6,330,345 B1
• Filed: 11/17/1997
• Issued: 12/11/2001
• Est. Priority Date: 11/17/1997
• Status: Expired due to Term

• Current Assignee: Apple Inc.
• Original Assignee: Veridicom, Inc. (Veridicom International, Inc.)
• Inventors: Russo, Anthony P., OʼGorman, Lawrence
• Primary Examiner(s): Bella, Matthew C.
• Assistant Examiner(s): CHAWAN, SHEELA C
• Application Number:
  US08/971,455
• Time in Patent Office: 1,485 Days
• Field of Search: 382/115, 382/124, 382/125, 382/126, 382/127, 382/318, 382/319, 382/312, 382/274, 382/275, 348/218, 348/229, 358/504, 358/483, 358/446, 358/463
• US Class Current: 382/115
• CPC Class Codes: G06V 10/993 Evaluation of the quality of the acquired pattern
• CPC Class Codes: G06V 40/1306 non-optical, e.g. ultrasonic or capacitive sensing
• CPC Class Codes: G06V 40/1347 Preprocessing; Feature extraction

Abstract

A system and method for automatically determining a set of default settings (with respect to a blank image) so that a uniform and high contrast image results when, for example, a finger is present on a sensor device. A background noise image and other diagnostic data, such as non-functional areas, are also automatically determined with respect to the blank image and stored for future reference. The above processing is performed each time the sensor device is initialized. Once the initialization process is complete, the individual places the required biometric feature, for example, a finger on the sensor device. The methodology adjusts the set of default settings to account for the condition of the biometric feature being imaged by increasing or decreasing the sensitivity level of the sensor device. The determination of optimum sets is achieved by analyzing specific regions of the image data rather than the entire image. The present invention then captures multiple images at different sensitivity levels since a specific region may be optimized with respect to one set of settings and another region may be optimized with respect to another set of settings. The diagnostic data is then used to correct the captured images by substituting any non-functional areas in the sensor device with average intensity values from neighboring regions. The multiple images are then combined to form a resultant image by using a weighted and intensity-transformed combination of regions from the different images.

Claims

1. A method for sensing and analyzing an individual feature, said method comprising the steps of:

automatically determining a set of default settings for a sensor device based on a blank image;

automatically adjusting said set of default settings based on variable conditions that may be present when capturing an image of the individual feature;

capturing multiple images at a corresponding set of settings; and

,

combining said multiple images to form a resultant image,

wherein said step of automatically adjusting includes the steps of;

forming at least one set of settings that are optimized for the individual feature; and

,

forming at least one additional set of settings that are optimized for the individual feature;

said capturing step including;

capturing a corresponding image for each of said at least one set of settings; and

,

capturing an additional corresponding image for each of said at least one additional set of settings;

said combining step including;

combining said corresponding image with said additional corresponding image to form said resultant image.

2. The method according to claim 1, wherein said step of combining includes the steps of:

determining an intensity shift value for each of a plurality of regions comprising said corresponding image and said additional corresponding image; and

,

determining an intensity range for said each region,

wherein said intensity shift value and said intensity range are used such that each pixel in said each region maximally occupies an available intensity range in said resultant image.

3. A method for sensing and analyzing an individual feature, said method comprising the steps of:

automatically determining a set of default settings for a sensor device based on a blank image;

automatically adjusting said set of default settings based on variable conditions that may be present when capturing an image of the individual feature;

capturing multiple images at a corresponding set of settings;

combining said multiple images to form a resultant image; and

correcting each of said multiple images with stored diagnostic data,

wherein said step of combining utilizes intensity translated weighting to obtain said resultant image.

4. A method for sensing and analyzing an individual feature, said method comprising the steps of:

automatically determining a set of default settings for a sensor device based on a blank image;

automatically adjusting said set of default settings based on variable conditions that may be present when capturing an image of the individual feature;

capturing multiple images at a corresponding set of settings; and

combining said multiple images to form a resultant image, wherein said determining step includes the steps of;

dividing an image area of said sensor device into at least two regions;

calculating average intensity values for said regions;

computing a variance for each of said regions; and

adjusting sensor device settings until the minimum intensity in an original intensity range of each said region is translated to zero and said original range is expanded to occupy a full intensity range for each said region.

5. A method for sensing and analyzing an individual feature, said method comprising the steps of:

automatically determining a set of default settings for a sensor device based on a blank image;

automatically adjusting said set of default settings based on variable conditions that may be present when capturing an image of the individual feature;

capturing multiple images at a corresponding set of settings; and

combining said multiple images to form a resultant image,

wherein the step of automatically determining includes the steps of;

analyzing at least one histogram of partially captured data corresponding to at least one set of adjusted settings; and

selecting at least one set of settings based on said at least one histogram.

6. An apparatus for sensing and analyzing an individual feature, said apparatus comprising:

a processor for analyzing at least two sets of image data;

a sensor for providing said at least two sets of image data to said processor;

said processor determining automatically a set of default settings for said sensor based on a blank image;

said processor adjusting automatically said set of default settings based on variable conditions that may be present when capturing an image of the individual feature; and

,

means for combining said at least two sets of image data to form a resultant image,

wherein said processor includes;

diagnostic correction means for correcting each of said multiple sets of image data with stored diagnostic data,

wherein said multiple sets of image data are comprised of multiple regions, wherein said means for combining combines said multiple sets of image data region by region using intensity translated weighting for each of said multiple regions to obtain said resultant image.

12. The device according to claim 6, wherein said processor includes an analyzer for examining contrast levels of partially captured fingerprint image data from said sensor.

13. The device according to claim 6, wherein said processor includes an analyzer for examining fingerprint image contrast levels by looking at grey levels of partially captured fingerprint image data.

7. An apparatus for sensing and analyzing an individual feature, said apparatus comprising:

a processor for analyzing at least two sets of image data;

a sensor for providing said at least two sets of image data to said processor;

said processor determining automatically a set of default settings for said sensor based on a blank image;

said processor adjusting automatically said set of default settings based on variable conditions that may be present when capturing an image of the individual feature; and

,

means for combining said at least two sets of image data to form a resultant image,

wherein said processor includes;

diagnostic correction means for correcting each of said multiple sets of image data with stored diagnostic data,

wherein said means for combining includes;

means for determining an intensity shift value for each region comprising said multiple sets of image data; and

,

means for determining an intensity range for said each region,

wherein said processor uses said intensity shift value and intensity range such that each pixel in said each region maximally occupies an available intensity range in said resultant image.

8. An apparatus for sensing and analyzing an individual feature, said apparatus comprising:

a processor for analyzing at least two sets of image data;

a sensor for providing said at least two sets of image data to said processor;

said processor determining automatically a set of default settings for said sensor based on a blank image;

said processor adjusting automatically said set of default settings based on variable conditions present when capturing an image of the individual feature; and

means for combining said at least two sets of image data to form a resultant image,

wherein said processor includes

means for calculating average intensity values for at least two regions comprising an image area of said sensor;

means for computing a variance for each of said regions to establish uniformity across said image area; and

means for adjusting sensor device settings until the minimum intensity in an original intensity range of said blank image is translated to zero and said original range is expanded to occupy a full intensity range such that maximum contrast capability is provided.

9. A solid state fingerprint sensing device for sensing and analyzing a fingerprint, comprising:

a solid state sensor for providing fingerprint image data; and

a processor for analyzing said fingerprint image data, said processor determining automatically a set of default settings for said sensor based on a blank image;

said processor including adjustment means for adjusting automatically said set of default settings based on variable conditions present when capturing a fingerprint image of the fingerprint;

said processor including diagnostic correction means for storing diagnostic data collected from said sensor based on the blank image, said diagnostic correction means correcting at least one set of fingerprint image data received form said sensor when said sensor is set with at least one set of adjusted settings,

said processor including means for combining said at least one set of fingerprint image data with at least one additional set of fingerprint image data to form a resultant image, said at least one additional set of fingerprint image data corresponding to at least one additional set of adjusted settings, wherein said at least one additional set of adjusted settings differs from at least one other set of settings.

10. The device according to claim 9, wherein said fingerprint image data comprises multiple regions, said means for combining using intensity translated weighting for each of said multiple regions to combine said at least one set of fingerprint image data with said at least one additional set of fingerprint image data.

11. The device according to claim 9, wherein said means for combining combines said multiple sets of fingerprint image data by taking an average of said multiple sets of fingerprint image data to obtain said resultant image.

14. The device according to claim 9, wherein said adjustment means captures at least two regions of data from multiple regions of fingerprint image data and creates a grey level histogram of said at least two regions of data to examine contrast levels of the fingerprint image captured.

15. The device according to claim 9, wherein said diagnostic correction means corrects said at least one set of fingerprint image data received from an optimally set sensor by substituting non-functional areas of pixels with average intensity values from neighboring pixels.

16. The device according to claim 9, wherein said diagnostic correction means maintains a history file for said diagnostic data to track sensor degradation.

17. The device according to claim 9, wherein said processor subtracts out a background noise image from said at least one set of fingerprint image data.

18. A method for sensing and analyzing an individual feature, said method comprising the steps of:

automatically determining a set of default settings for a sensor device based on a blank image;

automatically adjusting said set of default settings based on variable conditions that may be present when capturing an image of the individual feature;

capturing multiple images at a corresponding set of settings; and

combining said multiple images to form a resultant image,

wherein at least one of the corresponding set of settings differs from at least one other corresponding set of settings, including the further step of weighting the images according to quality parameters.

19. A method for optimizing an image of an individual feature, comprising the steps of:

determining a set of default settings for a sensor device;

capturing a first image of the individual feature at a first set of settings;

capturing at least one additional image of the individual feature at a differing set of settings;

weighting the captured images according to quality parameters; and

combining the weighted images to form a resultant image.

20. An apparatus for sensing and analyzing an individual feature, said apparatus comprising:

a processor for analyzing at least two sets of image data;

a sensor for providing said at least two sets of image data to said processor;

said processor determining automatically a set of default settings for said sensor based on a blank image;

said processor adjusting automatically said set of default settings based on variable conditions that may be present when capturing an image of the individual feature; and

,

means for combining said at least two sets of image data to form a resultant image,

wherein the two sets of image data differ from each other and wherein the means for combining the at least two sets of image data includes the processor executing instructions, the processor further operable to weight the image data according to quality parameters and to combine the weighted images.