Composite Laminate Fingerprint Verification Without Physical Tags
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Solution Overview
Problem
In composite laminate manufacturing, existing methods lack efficient and reliable means to verify the identity and similarity of composite laminate layers or plies without physical tags or labels, leading to potential errors in material identification and layup processes.
Innovation Solution
A method and system for generating fingerprints of reference objects by capturing images from multiple angles, removing lighting effects, and comparing candidate object fingerprints with reference fingerprints to determine correlation, using a signal processor and detector with lenses to analyze and process images, allowing for verification of object identity or similarity without physical tags.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical tags or labels are used to identify objects, then object identification is straightforward and reliable, but the manufacturing process becomes more complex and requires additional components
Solution Approach 1:
The patent creates optical copies (images) of objects and their identifying features instead of using physical tags. A fingerprinting system captures images of objects from multiple angles, extracts unique visual features, and stores them as reference data. This allows identification through image comparison rather than physical tagging, eliminating the need for additional physical components while maintaining reliable identification.
Solution Approach 2:
The patent replaces mechanical/physical tagging systems with an optical and computational system. Instead of attaching physical labels and reading them optically, the system uses image capture, digital feature extraction, and algorithmic comparison to identify objects. This substitution eliminates physical components and their associated complexity while improving reliability through digital verification.
2Adaptability or versatility
If images are captured under different lighting conditions, then the system can operate in various environments, but lighting effects create noise that reduces verification accuracy
Solution Approach 1:
The patent extracts and removes lighting effects from captured images through image processing techniques. The system separates the actual object features from lighting-induced artifacts by analyzing multiple images taken under different lighting conditions. This extraction process isolates the invariant object characteristics while eliminating the variable lighting effects, allowing accurate verification across different environmental conditions.
Solution Approach 2:
The patent performs preliminary image processing to remove lighting effects before fingerprint extraction and comparison. By preprocessing the images to eliminate lighting variations beforehand, the system ensures that subsequent fingerprint matching is based solely on object characteristics. This preliminary action prepares the data in advance, enabling accurate verification regardless of when or under what lighting conditions the comparison occurs.
3Measurement precision
If multiple images are captured from different angles to create comprehensive fingerprints, then verification accuracy improves, but the processing time and computational complexity increase
Solution Approach 1:
The patent divides the fingerprinting process into distinct segments: image capture from multiple angles, feature extraction from each image, fingerprint generation by combining features, and comparison. This segmentation allows the system to process multiple angle images systematically, extracting only the essential identifying features from each view rather than processing entire images. The segmented approach manages computational complexity while maintaining comprehensive verification accuracy.
Data Source
AI summary
Disclosed herein are methods and systems for generating a fingerprint for verification of a reference object, such as a layer or ply during a composite laminate layup procedure. An exemplary method includes generating a plurality of images of the reference object from a plurality of angles, removing at least one lighting effect from at least one reference image to generate at least one processed image, generating a reference fingerprint for the reference object based on the at least one processed image, generating at least one candidate image of a candidate object, generating a candidate fingerprint for the candidate object based on the at least one candidate image, comparing the candidate fingerprint and the reference fingerprint to determine whether a correlation exists between the candidate fingerprint and the reference fingerprint, and generating an alert based on the comparison of the candidate fingerprint and the reference fingerprint.