Digital Data Minutiae Extraction for Cultural Artefact Authentication
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Solution Overview
Problem
Current computer-assisted analysis and reassembly of cultural artefacts face challenges due to the vast amount of data generated by existing systems, particularly in the reassembly of three-dimensional archaeological fragments and authentication of artworks, which becomes impractical with the proliferation of scanning and imaging technologies.
Innovation Solution
A method utilizing a multimodal digital imaging device for non-invasive scanning at photonic-, nano-, or molecular levels, followed by algorithmic transformation and analysis to identify and compare digital data minutiae, allowing for efficient data reduction and correlation-based characterization of cultural artefacts, including authentication and reassembly processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple scanning and imaging technologies are used to analyse cultural artefacts, then measurement precision and data completeness are improved, but the quantity of data generated increases significantly, making analysis impractical
Solution Approach 1:
The patent segments the large volume of scanning and imaging data into distinct categories (geometric data, texture data, color data, etc.) and processes each category separately through specialized analysis algorithms. This segmentation allows the system to handle multi-modal data from various imaging technologies without being overwhelmed by the total data volume, as each segment can be processed independently and efficiently.
Solution Approach 2:
The patent extracts and isolates specific features and characteristics from the comprehensive data set generated by multiple imaging technologies. By extracting only the relevant and meaningful data elements (such as specific geometric features, texture patterns, or color signatures) rather than processing the entire data set, the system achieves high measurement precision while avoiding the impracticality of analyzing all generated data.
2Reliability
If comprehensive scanning data is collected from multiple imaging technologies, then authentication accuracy is improved, but the complexity of data processing and analysis increases
Solution Approach 1:
The patent introduces an intermediary processing layer that receives data from multiple imaging technologies and transforms it into a standardized format suitable for authentication analysis. This intermediary layer includes modules for data normalization, feature extraction, and correlation analysis that bridge the gap between diverse imaging data sources and the authentication decision-making process, thereby managing complexity while maintaining accuracy.
Solution Approach 2:
The patent transforms the raw data from multiple imaging technologies by changing its parameters and representation form. Different imaging modalities are converted into comparable parameter sets (such as geometric descriptors, texture metrics, color histograms) that can be systematically analyzed together. This parameter transformation reduces processing complexity by creating a unified analysis framework while preserving the distinctive information from each imaging technology.
3Manufacturing precision
If detailed digital data models are created from fragments, then reassembly precision is improved, but the time required for data analysis and comparison increases
Solution Approach 1:
The patent performs preliminary processing of fragment data during the scanning and modeling phase, pre-calculating and storing key geometric features, surface characteristics, and potential matching indicators. By preparing and organizing this information in advance, the system reduces the computational burden during the actual reassembly process, allowing for high-precision matching without excessive analysis time when fragments need to be reassembled.
Data Source
AI summary
This invention relates to means and processes of analysing cultural artefacts, for example to authenticate works of art or to reconstruct fragmented archaeological artefacts digitally, by first scanning the target artefact to produce a digital data model of the target artefact, which is then transformed algorithmically to obtain a target digital transform. This is analysed to identify and extract digital data minutiae from the digital transform data. Then, a number of comparator artefacts are scanned using the same scanning technologies to produce a digital data model of each comparator artefact. The same processes of algorithmic transformation and digital data minutiae extraction are applied to the comparator digital data models. An algorithmic comparison is then made between the target digital data minutiae and the comparator digital data minutiae to identify correlating comparator and target digital data minutiae in accordance with predetermined correlation criteria and the artefact is characterised according to the degree of correlation, for purposes of authentication or digital reconstruction, for example.