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(Spring 2013) The Impact of Dirty Fingerprints
 

(Spring 2013) The Impact of Dirty Fingerprints

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The focal point of our project is to compare the differences between dirty fingerprints and cropped fingerprints using the data we have collected. During the procedure we captured three clean and ...

The focal point of our project is to compare the differences between dirty fingerprints and cropped fingerprints using the data we have collected. During the procedure we captured three clean and three dirty fingerprints from each person in the group. We then analyzed the score, minutiae points, core/delta, good and poor quality of each of the fingerprints. The importance of this project is to analyze the impact of dirty fingerprints on quality.

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    (Spring 2013) The Impact of Dirty Fingerprints (Spring 2013) The Impact of Dirty Fingerprints Document Transcript

    • THE IMPACT OF DIRTY FINGERPRINTS The focal point of our project is to compare the differences between dirty fingerprints and cropped fingerprints using the data we have collected. During the procedure we captured three clean and three dirty fingerprints from each person in the group. We then analyzed the score, minutiae points, core/delta, good and poor quality of each of the fingerprints. The importance of this project is to analyze the impact of dirty fingerprints on quality. Connor Dawes, Clark Ford, Ben Petry, Michael Brockly, Stephen Elliott Overview Subject 1 Clean Dirty Subject 2 Clean Dirty Subject 3 Clean Dirty Cropped Fingerprints • Cropped fingerprints rely on taking an already whole print and cutting a certain portion or percentage out • Scanner technology is not a factor • Past research has been done to ID artificial poor quality prints, but only by cropping the image post-collection • The purpose of cropping is to see what percent of the fingerprint can be missing and the system still make a positive ID Dirty Fingerprints • Many variables that may impact the scanners’ ability to function (dryness, grit, grade of soil, etc.) • A large factor is the scanners’ limitations of collecting viable data points from a low quality fingerprint • More realistic effect to real world operating conditions • No formal research was found on this topic, possibly due to the difficulty in quantifying “dirtiness” • A dirty fingerprint has random data destruction VS. VS. GATHERED DATA Clean Fingerprints Dirty Fingerprints Average Minutiae Points 60.66 55.78 Average Good Score 450.67 371.89 Average Poor Score 136.89 225.78 Average Core/Delta ID 1.33 0.33 The above data represents a test of three individuals. The quantity of poor quality pixels from scans of dirty prints was much higher as indicated from the above graph. The number of usable minutiae points tended to not follow an exact model. We believe this is due to foreign material creating false minutiae points. Minutiae Points = The number of identified minutiae points in the image that can be used Good Score = The number of usable pixels in the image Poor Score = The number of unusable pixels in the image Core/Delta ID = The number of identified cores and deltas in the image Below is an example of matching a cropped portion of an image to the original Below is an example of matching a randomly altered (dirty) image to the original Source: http://www.aware.com/biometrics/qualitycheck.html