Fingerprint Reco

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Title and Author

  • Fingerprint RecognitionMokhled S. AlTarawnehMutah University, Faculty of Engineering, Computer Engineering Department, Mutah 61710, Jordanmokhled@mutah.edu.joDate: 23/07/2023


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Introduction to Fingerprint Recognition

  • Fingerprint recognition is an established and extensively researched area of biometrics.

Biological Principles

  • Unique epidermal ridges and furrows characterize each fingerprint.

  • Varying configurations allow systematic classification while maintaining individual uniqueness.

  • These configurations are permanent, with only minor changes due to injury.


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Fingerprint Formation

  • Formed by seven months of fetus development, and configurations remain unchanged unless traumas occur.

  • Genetic similarities:

    • Unrelated individuals show minimal similarity.

    • Parent-child similarities exist, with siblings showing greater resemblance.

    • Identical twins exhibit the highest similarity.


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Fingerprint Sensors

  • KINETIC SCIENCES INC. KC-901 sensor setup for integration.

Design Specifications

  • Chip-on-Board package.

  • 20-pin Dual-inline Ceramic Package (DIP20).


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Types of Fingerprint Sensors

  • Optical

  • Silicon-Based Capacitive

  • Ultrasound

  • Thermal


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Optical Sensors

  • Widely used and oldest technology.

  • Utilizes a coated plastic plate for image capture via CCD.

  • Automatic/manual brightness adjustments improve image quality.


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Advantages and Disadvantages of Optical Sensors

Advantages

  • Proven performance.

  • Temperature resistant.

  • Cost-effective.

  • High resolution (up to 500 dpi).

Disadvantages

  • Large sensing plates needed.

  • Residual prints can degrade image quality.

  • Sensitivity to wear affecting accuracy.


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Silicon-Based Sensors

  • Gained popularity since the late 90s.

  • Operate mostly on DC Capacitance, some on AC Capacitance.

  • Measures capacitance to create a grayscale digital image.


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Functioning of Silicon-Based Sensors

  • Fingerprint cards have capacitive plates measuring capacitance with fingertip.

  • Weak electrical charges create patterns representing ridges/valleys, which are digitized for processing.


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Direct vs. Active Capacitive Measurement

Direct Capacitive Measurement

  • Measures raw contact.

Active Capacitive Measurement

  • Protective coating enhances signal response.


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Advantages and Disadvantages of Silicon-Based Sensors

Advantages

  • High resolution from miniaturization.

  • Cost-effective due to lower manufacturing costs.

Disadvantages

  • Durability under adverse conditions not fully proven.


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Ultrasound Sensors

  • Most accurate fingerprint technology.

  • Measures distance by transmitting ultrasound waves, factoring in impedance variations.


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Advantages and Disadvantages of Ultrasound Sensors

Advantages

  • Capable of function under dirty or oily conditions.

  • Combines optical and silicon technology strengths.

Disadvantages

  • Image quality highly dependent on sensor contact quality.


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Thermal Sensors

  • Utilize Pyro Electric materials to capture temperature differences.

  • Measures temperature differentials to distinguish fingerprint ridges and valleys.


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Advantages and Disadvantages of Thermal Sensors

Advantages

  • Immune to electrostatic discharge.

  • Functions well in extreme temperatures.

Disadvantages

  • Rapid thermal equilibrium leads to fast image loss.


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Fingerprint Classification

  • Large databases (e.g., FBI has 70 million fingerprints) necessitate classification for efficient matching.

Classification Types

  • Includes whorl, loop, arch configurations.


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Line Types Classification

  • Arch Prints: Majority pattern types.

  • Loop: Enters and exits the same side.

  • Whorl: Circular patterns; important for identification.

  • Bifurcation, Island, Tented Arch, Spiral, Rod classifications enhance detail recognition.


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Automatic Verification System

Steps Involved

  1. Image acquisition

  2. Preprocessing

  3. Stored template comparison

  4. Feature extraction

  5. Template matching and registration.


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Feature Extraction

  • Details various ridge patterns.

Classification System

  • Based on Henry system: left loop, right loop, arch, whorl, tented arch.

  • Loops comprise about 2/3 of fingerprints.


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Enhancement Techniques

  • Obtain clear images, enhance ridge clarity, and apply thinning algorithms.


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Minutiae Localization

  • Filters false minutiae and identifies true patterns.

  • Coordinates and angles of minutiae are crucial for matching accuracy.


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Template Selection Variability

  • Stability of biometric data varies with user interaction, sensor changes, and environmental factors.


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Template Storage Strategy

  • Store multiple templates to enhance recognition accuracy while managing database overhead.


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Automatic Minutiae Detection (AMD)

  • Critical process for quality fingerprint extraction; compares minutiae between images.


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Matching Algorithm Process

  • Steps include marking minutiae points and comparing input image to stored database images.


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Problems with AMD

  • Low accuracy with poor quality fingerprints; does not account for global ridge patterns.


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FX3 Algorithm

  • Innovative algorithms for fingerprint processing, providing security and efficiency.


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Accuracy Metrics

  • FAR: False Accept Rate

  • FRR: False Reject Rate

  • EER: Equal Error Rate (lower is better).


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Research Issues

  • Focus on improving security and system performance (FAR & FRR).


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Multibiometric Systems

  • Combine multiple biometric traits for enhanced reliability and security.


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Attacks on Biometric Systems

  • Risks include data database attacks and input port vulnerabilities.


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Spoofing Attacks

  • Process where fake biometric samples deceive systems; methods include mold casting and photographic techniques.


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Solutions to Attacks

Hardware Solutions

  • Measurement of physiological traits (e.g., temperature, pulse).

Software Solutions

  • Detect moisture patterns resulting from perspiration.


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Third Level Detail Research

  • Focuses on detailed analyses of fingerprint pores and outlines.


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Enhancement Techniques for Quality

  • Use of filters and image processing to improve fingerprint quality for analysis.


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Applications of Fingerprint Recognition

  • Various applications: banking security, physical access control, identification systems, etc.


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Market Share by Technology

  • Comparative share: Finger-scan leads at 48.8%, followed by facial-scan, hand-scan, etc.


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Latest Technologies

Fingerprint Registry Service

  • Centralized service for affordable fingerprint technology.

Compaq Fingerprint Identification Technology

  • Affordable biometric tech to replace passwords with fingerprints.


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References

  • Comprehensive list of research and resources in fingerprint recognition.