Artificial Fingerprint Encoding for Damage-Resistant Data Capture
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Solution Overview
Problem
Existing two-dimensional codes are vulnerable to damage, difficult to extract information from partial codes, and susceptible to cyberattacks, while biometric fingerprints require special devices and pose privacy risks.
Innovation Solution
Encoding data using artificial fingerprints generated from minutiae templates of human fingerprints, which include ridge discontinuities, orientations, and locations, allowing for machine-readable images that can be scanned with common devices and are robust to damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing two-dimensional codes (QR codes, matrix codes) are used for data encoding, then data can be encoded and scanned with mobile device cameras, but the codes are vulnerable to damage and difficult to extract information from partial or damaged codes
Solution Approach 1:
The patent segments the data encoding into multiple distributed minutiae points across the fingerprint image. Each minutiae point contains encoded information about ridge discontinuities, orientations, and locations. This segmentation allows the system to tolerate damage to individual points while maintaining overall code readability, as the distributed nature ensures redundant information is available across multiple locations.
Solution Approach 2:
The patent creates an artificial fingerprint that replicates the structural characteristics of real fingerprints (ridges, valleys, minutiae points) but encodes data within these structures. The artificial fingerprint copies the visual appearance and structural properties of human fingerprints, allowing it to be read by standard fingerprint scanning devices while providing enhanced robustness through the encoded minutiae point system.
2Ease of manufacture
If existing two-dimensional codes are used, then data encoding is simple, but the codes are susceptible to tampering and cyberattacks
Solution Approach 1:
The patent applies local quality by encoding specific data characteristics into the local properties of minutiae points (such as ridge discontinuity patterns, orientations, and precise locations). Each minutiae point carries encoded information that is locally embedded in the fingerprint structure. This local encoding makes tampering difficult because any modification would require precise manipulation of multiple minutiae point properties simultaneously, while the overall encoding process remains relatively simple.
3Reliability
If biometric fingerprints are used for data encoding, then the codes are difficult to damage and secure, but special devices are required and privacy risks exist
Solution Approach 1:
The patent creates an artificial fingerprint that serves multiple functions: it provides the security and damage resistance of biometric fingerprints while being compatible with standard fingerprint scanning devices. The artificial fingerprint uses the same visual characteristics (ridges, valleys, minutiae points) that standard devices are designed to read, eliminating the need for special equipment. It simultaneously provides data encoding capabilities with enhanced security properties.
4Reliability
If biometric fingerprints are used for data encoding, then secure data storage is achieved, but privacy concerns arise
Solution Approach 1:
The patent extracts the essential security features needed for secure data encoding and separates them from the actual biometric data. Instead of using real fingerprint images that contain personal identifiable information, the system extracts only the necessary encoded information (minutiae point characteristics) and embeds it in an artificial fingerprint structure. This extraction process eliminates privacy concerns by not storing or processing actual biometric data while maintaining the security benefits through the encoded minutiae point system.
Data Source
AI summary
Systems and methods for encoding data in a machine-readable image (e.g., an artificial fingerprint) are disclosed. The methods include segmenting a plurality of bits included in a bit stream to be encoded into a plurality of blocks such that each block includes two or more of the plurality of bits. The plurality of blocks are used to generate a minutiae template comprising a plurality of minutiae points each of which is representative of a local ridge discontinuity in a fingerprint, and is associated with a location and an orientation. An artificial fingerprint is generated from the minutiae template, and stored in association with the bit stream. The artificial fingerprint encodes the bit stream and comprises a plurality of ridges and a plurality of valleys.