Autonomous Collectible Grading System Using Machine Vision
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Solution Overview
Problem
Current card grading systems rely on human evaluation, which is subjective, inconsistent, and labor-intensive, leading to fluctuations in grading results and potential misstatement of value, with collectors often resubmitting cards for higher grades, causing issues like 'grade inflation' and lack of confidence in the market.
Innovation Solution
A fully autonomous system using electromechanical platforms and machine learning algorithms for image processing, capable of capturing and analyzing multiple images of collectibles, assessing their condition, and assigning grades without human intervention, incorporating features like rotational and translational freedom, sensory units, and deep learning techniques for accurate defect identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If human evaluation is used for card grading, then the grading process can be performed with simple equipment, but the grading results are subjective, inconsistent, and labor-intensive
Solution Approach 1:
The patent replaces the mechanical human eye evaluation system with an automated optical imaging and computer processing system. Multiple high-resolution cameras capture images of the card from different angles, and image processing algorithms automatically analyze centering, corners, edges, and surface conditions, eliminating human subjectivity while maintaining comprehensive inspection capability.
Solution Approach 2:
The grading process is segmented into distinct functional modules: image capture subsystem with multiple cameras positioned at specific angles, image processing subsystem that separates analysis into centering evaluation, corner condition, edge condition, and surface defect detection, and grading calculation subsystem. This segmentation enables each module to specialize in specific aspects of card condition assessment.
2Device complexity
If human graders are used, then the system can operate with simple equipment, but the productivity is low and labor-intensive
Solution Approach 1:
The automated system enables continuous operation without interruption by eliminating the need for grader fatigue management, breaks, or shifts. The imaging and processing system can evaluate cards at a consistent rate around the clock, with the electromechanical platform automatically positioning and repositioning cards for continuous throughput, achieving sustained high-speed operation.
Solution Approach 2:
The system performs self-grading without human intervention. The automated image capture, processing, and analysis components work autonomously to evaluate card condition and assign grades, eliminating the need for human labor in the actual grading process while maintaining consistent quality standards.
3Measurement precision
If multiple graders evaluate the same card, then more comprehensive assessment is possible, but grade inflation and resubmission issues occur
Solution Approach 1:
The system provides detailed feedback through comprehensive imaging that captures all card surfaces and conditions from multiple angles. The image processing generates objective data about centering percentages, corner sharpness, edge conditions, and surface defects, creating a transparent grading basis that eliminates the need for multiple subjective evaluations and reduces resubmission incentives.
Data Source
AI summary
Embodiments relate to a system, comprising, an electromechanical platform for positioning and orienting a collectible to capture a plurality of images by an image capturing device of at least a first side and a second side of the collectible, a computer comprising at least one processor comprising computer-executable instructions stored on one or more computer-readable media, wherein the computer is operable to receive the plurality of images of the collectible, at least one processing routine comprising an image processing algorithm for a condition assessment of the collectible applied to at least one image from the plurality of images by at least one processor to obtain a raw data of the condition of the collectible, a device for encapsulating the collectible in a tamper proof casing and stamping at least one or more labels on the tamper proof casing, wherein the stamping of the at least one or more labels is at a specified location on the tamper proof casing; and wherein the system is operable to be fully autonomous.