AI Image Provenance Analysis for Faster Object Authentication
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Solution Overview
Problem
Existing methods for verifying the authenticity and origin of valuable objects, such as collectibles and luxury items, are costly, time-consuming, and prone to human error, making it difficult to authenticate objects worth thousands of dollars effectively and efficiently.
Innovation Solution
A system and method using digital image data and artificial intelligence models to determine the provenance and surface status of objects by comparing user-submitted images with stored datasets, providing authentication and origin scores based on image analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If expert analysis is used to verify object authenticity and origin, then reliability of authentication is improved, but cost and time consumption increase significantly
Solution Approach 1:
The patent creates a digital copy (photograph) of the object and uses AI models to analyze this copy instead of requiring physical inspection by experts. This allows multiple AI analysts to simultaneously examine the same digital copy, dramatically reducing authentication time while maintaining reliability through automated image analysis of provenance indicators.
Solution Approach 2:
The patent replaces the mechanical system of human expert inspection with an automated AI-based image analysis system. The AI models process digital photographs to identify provenance indicators, substituting human visual inspection and decision-making with automated computational analysis, thereby reducing time consumption while maintaining authentication reliability.
2Measurement precision
If expert analysis is used to verify object authenticity, then authentication accuracy is improved, but cost increases prohibitively for many objects
Solution Approach 1:
The patent uses a digital photograph as a copy of the object, eliminating the need for expensive physical expert inspection. The AI models analyze this digital copy to identify provenance indicators with high accuracy, making authentication cost-effective by replacing costly human expertise with automated image analysis that can process unlimited numbers of objects.
Solution Approach 2:
The patent enables the authentication system to serve itself by using AI models that automatically analyze images and identify provenance indicators without requiring human expert intervention. This self-service capability dramatically reduces costs while maintaining authentication accuracy through automated detection of key visual features and patterns.
3Reliability
If comprehensive information gathering is performed to verify object provenance, then authentication reliability is improved, but time consumption and cost increase
Solution Approach 1:
The patent extracts only the essential provenance indicators from the complete object image, rather than requiring comprehensive information gathering about every aspect of the object. The AI models identify and extract key visual features that are sufficient for authentication, reducing information processing load while maintaining verification reliability by focusing on the most diagnostic characteristics.
Solution Approach 2:
The patent creates a digital copy of the object and uses AI to extract relevant provenance information from this copy, eliminating the need for physical examination and comprehensive data collection. This approach reduces information processing load by working with a static digital image while maintaining reliability through automated identification of key provenance features.
4Reliability
If human experts perform authentication, then nuanced judgment is improved, but human error and bias increase
Solution Approach 1:
The patent replaces the human decision-making system with an automated AI-based image analysis system. This substitution eliminates human error and bias by using consistent, objective algorithms to evaluate provenance indicators. The AI models provide reliable and consistent authentication results without being subject to human fatigue, prejudice, or motivational factors that can compromise judgment.
Solution Approach 2:
The patent enables the authentication system to make independent judgments without human intervention. The AI models autonomously analyze images, identify provenance indicators, and generate authentication results, eliminating human error and bias by replacing subjective human judgment with objective automated analysis that consistently applies the same evaluation criteria to all objects.
Data Source
AI summary
Systems, devices, and methods are disclosed for determining provenance (e.g., origin, authenticity) for an object using digital image data of one or more objects. A system receives, via a network, first digital image data of an object. The system determines from the first digital image data, a first set of feature variables, each corresponding to a characteristic of the object. The system determines, via an artificial intelligence model and with input including the first set of feature variables and a comparison dataset, an origin for the object. The artificial intelligence model generates, based on the portion of first feature variables that match corresponding portions of the comparison dataset, an output indicative of an origin. The system communicates, via the network, an indication of the provenance of the object.