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Fingerprint Matching Technology The Basics

Fingerprint Matching Technology The Basics. Overview. A wide variety of fingerprint matching software and hardware is available AuthenTec sensors can work with most varieties of matching systems including: AuthenTec supplied matchers Most independently available matchers

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Fingerprint Matching Technology The Basics

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  1. Fingerprint Matching TechnologyThe Basics

  2. Overview • A wide variety of fingerprint matching software and hardware is available • AuthenTec sensors can work with most varieties of matching systems including: • AuthenTec supplied matchers • Most independently available matchers • Fingerprint matchers are catagorized: • Primarily - by type of data used • Secondarily – by method of comparing that data

  3. What data is in a Fingerprint Image? • Ridge Patterns • Macro-features • Core, deltas, scars • Classical Ridge Minutia • Generalized Pattern • Specific ridge pattern • Fine Structure • Ridge shape • Lateral ridge shape • Vertical ridge shape • Local curvature • Pores (sweat glands)

  4. What data is in a Fingerprint Image? • Ridge Patterns • Macro-features • Core, deltas, scars • Classical Ridge Minutia • Generalized Pattern • Specific ridge pattern • Fine Structure • Ridge shape • Lateral ridge shape • Vertical ridge shape • Local curvature • Pores (sweat glands)

  5. What data is in a Fingerprint Image? • Ridge Patterns • Macro-features • Core, deltas, scars • Classical Ridge Minutia • Generalized Pattern • Specific ridge pattern • Fine Structure • Ridge shape • Lateral ridge shape • Vertical ridge shape • Local curvature • Pores (sweat glands)

  6. What data is in a Fingerprint Image? • Ridge Patterns • Macro-features • Core, deltas, scars • Classical Ridge Minutia • Generalized Pattern • Specific ridge pattern • Fine Structure • Ridge shape • Lateral ridge shape • Vertical ridge shape • Local curvature • Pores (sweat glands)

  7. How is this data best used?

  8. Commercial Fingerprint Matcher Trends • Take advantage of the higher powered processors and higher quality images to match with small-area sensors • Utilize smaller & denser features • That are now sufficiently repeatable (in images from the best quality sensors) for use in matching • to achieve accurate matching with small-area sensors • Multiple view compositing (mosaic building) • Permits flexible finger positioning even on very small sensors • Optimized for 1 to few matching • For personal computing and communication devices • Eliminates the complex structures used for large database searching and indexing

  9. For more information … Click here to learn how very small fingerprint sensors work Click here to learn about Specifying commercial biometric systems Back to Beginning

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