Digital Image Calibration Grid for Consistent Automated Imaging
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Solution Overview
Problem
Existing image calibration procedures for digital image acquisition systems are time-consuming and user-dependent, leading to inconsistent system calibration, which is a challenge for image processing and artificial intelligence applications.
Innovation Solution
An automated calibration method using a calibration target with identifiable features, computing distances between these features to generate a calibration grid, and adjusting system parameters based on comparisons between acquired and modeled images to achieve consistent image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual calibration procedures are used with color checkers, then calibration can be performed, but the process is time-consuming and user-dependent leading to inconsistent results
Solution Approach 1:
The system performs automated calibration by capturing images of the calibration target and automatically processing the image data to generate calibration parameters. The computer executes algorithms that identify calibration features, compute transformation matrices, and adjust system parameters without human intervention, enabling the system to calibrate itself rapidly and consistently
Solution Approach 2:
The patent replaces manual mechanical calibration operations with automated image processing and computational algorithms. Instead of physically positioning and manually analyzing calibration targets, the system uses digital image capture and automated feature detection to perform calibration, eliminating the need for manual mechanical adjustments
2Measurement precision
If extensive manual interaction is required for calibration, then precise positioning and identification can be achieved, but the process becomes user-dependent and inconsistent
Solution Approach 1:
The calibration system automatically captures images, identifies calibration features, computes transformation parameters, and adjusts system settings without requiring user intervention. The computer executes the entire calibration workflow autonomously, eliminating the need for operators to manually position targets or interpret calibration data
Solution Approach 2:
The system captures images of the calibration target, processes the image data to determine calibration parameters, and uses these parameters to adjust system settings. This closed-loop feedback mechanism ensures that calibration is based on actual measured data from the imaging system, improving precision while automating the process
3Adaptability or versatility
If different operators perform calibration manually, then various adjustments can be made, but different operators arrive at different system calibrations
Solution Approach 1:
The automated calibration system eliminates operator variability by having the computer execute the same calibration algorithms consistently for every calibration event. The system independently processes calibration images and generates calibration parameters without human judgment or manual adjustment, ensuring identical procedures are followed each time
Solution Approach 2:
The system automatically adjusts calibration parameters based on image analysis results. By changing calibration parameters through automated computation rather than manual operator input, the system maintains flexibility in adapting to different conditions while ensuring consistent, repeatable results across different operators and sessions
Data Source
AI summary
A method for calibrating a digital image acquisition system includes acquiring a digital image of a calibration target. Locations of each of a plurality of identifying features in the calibration target are determined and distances are computed between selected ones of the plurality of identifying features. A calibration grid is computed and overlay ed on the acquired digital image. The calibration grid is computed from a location of a reference one of the plurality of identifying features in the acquired digital image, the computed distances between the selected ones of the plurality of identifying features, and known locations of the plurality of calibration regions with respect to the reference one of the plurality of identifying features in the calibration target. The calibration grid specifies a plurality of calibration areas that correspond to the plurality of calibration regions in the calibration target.