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Enhancing Fingerprint Recognition with Region Information: A Novel Approach

Explore the concept of incorporating region information in minutiae matching for fingerprint recognition. This innovative idea aims to reduce the number of matches needed, improving the identification accuracy. The approach involves running binary tests on fingerprints to generate vectors that aid in matching prints with similar vectors, using Hamming distance for comparison. The current state includes code development for region detection and fingerprint thinning, with plans to test the model against a database of fingerprints and potentially adapt it for partial prints. Despite bugs in the code, the project shows promising progress towards a comprehensive solution.

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Enhancing Fingerprint Recognition with Region Information: A Novel Approach

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Presentation Transcript

  1. Fingerprint Recognition Professor Ostrovsky Andrew Ackerman

  2. The Idea • Including Region information in minutiae matching • Reduces amount of matches need • Can help better identify matches • Also, idea of Fingerprint of Fingerprint • Run X amount of binary tests on a fingerprint and return a vector of size X. This binary vector would identify the finger print • Matching prints would have similar vectors (hamming distance) • Tests could include information about minutiae as well as regions

  3. Current State • Rejected Idea of Topological Equivalence (for now). • Code Written for Region Detection • Code Written for Fingerprint Thinning • Multi Fingerprints Received • Though no Partial prints • Spring Break Checklist • Edge Enhancement code • Binarization Code

  4. Code So Far • Thinning code • Code to take in a binary object and “thin” it. • However, still bugs in code as well as “spurious” minutiae (minutiae created in thinning process)

  5. Region Detection Code • Works in O(n*m) – small constant in front • Colors in regions

  6. To do Spring Quarter • Test idea against database of fingerprints • Idea: Number of regions between matching minutiae will be similar • Write up results of Test • If time: • Explore idea of fingerprint of fingerprint • See if idea works for partial prints

  7. Assessment of Work • In all I think a good deal of work was done towards the project. Its seems most of the time was spent coming up with a novel idea that could be tested. I feel this project can easily be wrapped up by the end of spring quarter with a paper on the findings when including regions into the minutiae matching model of fingerprint recognition.

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