Automated Color Chart Detection and Orientation in Images
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Solution Overview
Problem
Current methods for color calibration in cameras and color reproduction systems require manual selection and orientation of color charts, limiting efficiency and flexibility, especially when charts are not horizontal.
Innovation Solution
An automated method to detect and orient embedded color charts within images, using grayscale conversion and scan line analysis to locate and verify the charts, reducing the search space from 5D to 2D and fixing the orientation for accurate calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection and orientation of color charts is used, then user control and precision in calibration is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system automatically detects and orients the color chart without user intervention. The computer identifies the chart's position and orientation angle autonomously, eliminating manual selection while maintaining calibration accuracy through automated image analysis and pattern recognition algorithms
Solution Approach 2:
The system performs preliminary detection of the color chart's orientation angle before calibration begins. By pre-identifying the chart's angular position and automatically adjusting image orientation, the system prepares the calibration data in advance, reducing subsequent processing time while ensuring precision
2Ease of operation
If color chart must be horizontal with image, then detection and calibration process is simplified, but adaptability to different orientations is reduced
Solution Approach 1:
The system dynamically adapts to the color chart's actual orientation in the image. Instead of requiring fixed horizontal placement, the system calculates the orientation angle and rotates the image or adjusts detection parameters accordingly, enabling operation with charts at any angle while maintaining detection simplicity through adaptive algorithms
Solution Approach 2:
The system changes the orientation parameter of the image based on detected chart angle. By automatically adjusting the image orientation parameter to align with the detected color chart, the system maintains simple detection processes while accommodating charts in various orientations, effectively resolving the contradiction between simplicity and flexibility
3Productivity
If automated detection method is implemented, then processing speed and efficiency are improved, but system complexity increases
Solution Approach 1:
The system replaces manual mechanical orientation adjustment with automated image processing algorithms. Computer vision techniques automatically detect the color chart's orientation angle and perform digital rotation, substituting complex manual operations with streamlined software-based solutions that increase speed while managing complexity through algorithmic automation
Data Source
AI summary
Methods and apparatuses for locating an embedded color chart in an image are described. In one exemplary method, an image that includes an embedded color chart is located without the intervention of the user. The embedded color chart is verified and used to create a color profile of the image. Furthermore, the orientation angle of the color chart is determined and the image orientation is fixed based on this angle.