Calibration and correction in a fingerprint scanner

• US 20040156555A1
• Filed: 10/23/2003
• Published: 08/12/2004
• Est. Priority Date: 08/09/1999
• Status: Active Grant

• Current Assignee: Cross Match Technologies Incorporated (Assa Abloy AB)
• Original Assignee: Cross Match Technologies Incorporated (Assa Abloy AB)
• Inventors: Irving, Richard D., Scott, Walter Guy
• Granted Patent: US 7,010,148 B2
• Time in Patent Office: Days
• US Class Current: 382/274
• CPC Class Codes: G06V 40/1335 Combining adjacent partial images (e.g. slices) to create a composite input or reference pattern; Tracking a sweeping finger movement
• CPC Class Codes: H04L 12/40117 Interconnection of audio or video/imaging devices home automation networks H04L12/2803; bitstream network arrangements specially adapted for distribution of digital video signals H04N7/24
• CPC Class Codes: H04L 12/40123 Interconnection of computers and peripherals printer information exchange with computer G06F3/1293

Abstract

A calibration and correction procedure for a fingerprint scanner. The calibration and correction procedure performs an automatic calibration procedure and gray level linearity procedure. The automatic calibration procedure includes a brightness function to correct for distortions in brightness, a focus check function to identify when the fingerprint scanner is out of focus, and a geometric distortion function to correct for imperfect linearity in the geometry of the fingerprint scanner. The gray level linearity procedure corrects for linear distortions in brightness and contrast of gray levels.

Claims

1. A method for calibration and correction of a fingerprint scanner, comprising the steps of:

(1) performing an auto-calibration procedure, wherein said auto-calibration procedure comprises at least one of the steps of;

(a) performing a brightness function to correct for distortions in brightness;

(b) performing a focus check function to identify when the fingerprint scanner is out of focus; and

(c) performing a geometric distortion function to correct for imperfect linearity in the geometry of the fingerprint scanner; and

(2) performing a gray level linearity procedure for providing a linear brightness and contrast response when taking fingerprints.

2. The method of claim 1, wherein step (1)(a) comprises the steps of:

(i) scanning a bright strip and a dark strip of a calibration target;

(ii) on a per-pixel basis, using bright and dark gray level values to compute an equation of a line;

(iii) determining correction coefficients for each pixel for normalizing the response of all pixels; and

(iv) storing the results in memory.

3. The method of claim 2, wherein step (i) comprises the steps of:

(1) scanning said bright and dark strips multiple times, resulting in multiple scans of said bright and dark strips; and

(2) averaging the multiple scans of said bright and dark strips to eliminate noise.

4. The method of claim 2, wherein step (ii) comprises the steps of:

(1) plotting a dark gray level value versus reflectivity for said dark strip;

(2) plotting a bright gray level value versus reflectivity for said bright strip; and

(3) determining the equation of the line for the dark and bright gray level values using an equation, y=mx+b, wherein m is a slope and b is a y-intercept.

5. The method of claim 2, wherein step (iii) comprises the steps of:

(1) subtracting an offset value from a measured pixel value, wherein said offset value is a y-intercept value for the equation of the line; and

(2) multiplying the result of step (1) above by a gain value to obtain a corrected pixel value, wherein said gain value is 1/m, wherein m is a slope of the equation of the line.

6. The method of claim 5, wherein step (2) further comprises the step of multiplying the corrected pixel value by α

, wherein α

is a multiplier for adjusting the overall brightness.

7. The method of claim 5, further comprising the step of storing the offset and gain values in memory.

8. The method of claim 1, wherein step (1)(b) comprises the steps of:

(i) scanning a focus strip of a calibration target;

(ii) generating a histogram of intensity versus gray level values from the focus strip; and

(iii) determining a quality factor Q for a bright peak in the histogram generated in step (ii), wherein the quality factor Q is the ratio of a height to a width at half amplitude of the bright peak.

9. The method of claim 8, further comprising the steps of:

(iv) comparing the quality factor Q to a threshold value; and

(v) generating an error message if the quality factor Q is less than the threshold value.

10. The method of claim 8, wherein step (i) comprises the steps of:

(1) scanning said focus strip multiple times, resulting in multiple scans of said focus strip; and

(2) averaging the multiple scans of said focus strips to eliminate noise.

11. The method of claim 8, wherein said focus test strip comprises three separate Ronchi rulings, each Ronchi ruling identifying different locations of a potential scan area or image area of a fingerprint scanner, and wherein step (i) comprises the step of scanning the three Ronchi rulings in said focus test strip separately, wherein step (ii) comprises the step of generating three histograms, one for each of the three Ronchi rulings, and wherein step (iii) comprises the step of determining the quality factor Q for each histogram for determining whether each location of the potential scan area is in focus.

12. The method of claim 1, wherein step (1)(c) comprises the steps of:

(i) scanning a geometry strip of a calibration target;

(ii) generating a geometric correction curve comprising a data point per pixel;

(iii) remapping each pixel using the geometric correction curve; and

(iv) generating an error message if data is out of bounds for correction.

13. The method of claim 12, wherein step (i) comprises the steps of:

(1) scanning said geometry strip multiple times, resulting in multiple scans of said geometry strip; and

(2) averaging the multiple scans of said geometry strip to eliminate noise.

14. The method of claim 12, wherein step (iii) comprises the steps of:

(1) determining a coefficient for each input pixel from the geometric correction curve;

(2) performing a reverse piecewise linear interpolation; and

(3) storing the results of said reverse piecewise linear interpolation in memory.

15. The method of claim 14, wherein step (2) comprises the steps of:

(a) remapping said input pixel to first and second new pixel locations, wherein said first new pixel location is the nearest whole number below said coefficient, and wherein said second new pixel location is the nearest whole number above said coefficient;

(b) determining maximum and minimum weighted grayscale values, wherein said maximum and minimum weighted grayscale values are based on said grayscale value of said input pixel weighted by first and second reflectivity values, wherein said first reflectivity value corresponds to a reflectivity value for a plurality of bright bars in said geometry strip, and wherein said second reflectivity value corresponds to a reflectivity value for a plurality of dark bars in said geometry strip;

(c) placing said maximum weighted grayscale value in said first new pixel location and said minimum weighted grayscale value in said second new pixel location if the absolute value of said first new pixel location minus said coefficient is less than the absolute value of said second new pixel location minus said coefficient; and

(d) placing said minimum weighted grayscale value in said first new pixel location and said maximum weighted grayscale value in said second new pixel location if the absolute value of said first new pixel location minus said coefficient is more than the absolute value of said second new pixel location minus said coefficient;

(e) repeating steps (a)-(d) for all input pixels; and

(f) summing grayscale levels for each remapped pixel.

16. The method of claim 1, wherein step (2) comprises the steps of:

(a) scanning a gray level test pattern;

(b) generating a curve of measured gray level values; and

(c) linearizing a measured gray level response.

17. The method of claim 16 wherein step (c) comprises the steps of:

(i) comparing measured gray level values with actual gray level values;

(ii) generating a difference vector, wherein said difference vector is the difference between the measured gray level values and the actual gray level values; and

(iii) storing said difference vector in memory for providing said linear brightness and contrast response when taking fingerprints.

18. The method of claim 1, wherein said step of performing said auto-calibration procedure comprises the step of performing said auto-calibration procedure on a daily basis and when requested by an operator.

19. The method of claim 1, wherein said step of performing said gray level linearity procedure comprises the step of performing said gray level linearity procedure at one of a factory, by a field technician at an on-site location, and by an operator at said on-site location.

20. A method for calibration and correction of a fingerprint scanner, comprising the steps of:

(1) performing an auto-calibration procedure, wherein said auto-calibration procedure comprises the steps of;

(a) performing a brightness function to correct for distortions in brightness;

(b) performing a focus check function to identify when the fingerprint scanner is out of focus; and

(c) performing a geometric distortion function to correct for imperfect linearity in the geometry of the fingerprint scanner; and

(2) performing a gray level linearity procedure for providing a linear brightness and contrast response when taking fingerprints.

21. A method for calibration and correction of a fingerprint scanner, comprising the step of:

performing an auto-calibration procedure, wherein said auto-calibration procedure comprises at least one of the steps of;

(a) performing a brightness function to correct for distortions in brightness;

(b) performing a focus check function to identify when the fingerprint scanner is out of focus; and

(c) performing a geometric distortion function to correct for imperfect linearity in the geometry of the fingerprint scanner.