Visual Marker Color Selection for Detectability
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Solution Overview
Problem
Existing visual markers, such as QR codes, face challenges in maintaining detectability across varying lighting conditions, printing/display conditions, and image sensor calibrations, leading to inconsistent performance and readability.
Innovation Solution
The method involves determining an initial set of colors for a visual marker based on environmental or object characteristics, and then selecting a subset of colors that are invariant to lighting and printing conditions, ensuring sufficient spatial separation in a 3D color space to maintain detectability, using a processor and memory-based systems to generate and encode data using these colors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional visual markers (QR codes) are used with fixed color schemes, then they are simple to generate and decode, but they fail to maintain detectability across varying lighting conditions, printing/display conditions, and image sensor calibrations
Solution Approach 1:
The system performs preliminary color space analysis and color selection before generating the visual marker. It pre-calculates the optimal color palette based on the target environment's lighting conditions, printing characteristics, and sensor response, ensuring the marker will be detectable under those specific conditions before it is even created.
Solution Approach 2:
The invention transitions from selecting colors in traditional 2D color space to operating in 3D color space (such as CIELAB or CIEXYZ). This additional dimension provides more degrees of freedom for color selection, allowing the system to find color combinations that maximize detectability while accounting for variations in lighting, printing, and sensor calibration.
2Reliability
If colors are selected to be invariant to lighting and printing conditions through sufficient spatial separation in 3D color space, then detectability is maintained across diverse environments, but the color selection process becomes more complex
Solution Approach 1:
The invention replaces manual or heuristic color selection methods with an automated computational system. The processor automatically analyzes the target environment characteristics, performs color space transformations, calculates optimal color palettes with sufficient spatial separation, and generates the visual marker without requiring manual intervention, thereby managing the complexity through automation.
Solution Approach 2:
The system dynamically adjusts color parameters (hue, saturation, lightness) in 3D color space to achieve optimal spatial separation between marker colors and background colors. By changing these parameters based on environmental analysis, the system ensures detectability while the automated process manages the complexity of the adjustments.
3Reliability
If environmental and object characteristics are analyzed to determine optimal color palettes, then visual markers remain detectable under specific conditions, but the generation process requires additional processing steps
Solution Approach 1:
The system performs environmental analysis and color palette optimization as preliminary steps before visual marker generation. By analyzing lighting conditions, printing characteristics, and sensor response upfront, the system ensures detectability is built into the marker design from the start, avoiding the need for multiple revision cycles and improving overall generation efficiency.
Solution Approach 2:
The automated color selection system serves itself by automatically analyzing environmental characteristics, determining optimal color palettes, and generating the visual marker without requiring manual iteration. This self-service approach streamlines the process by eliminating back-and-forth adjustments and manual optimization steps.
Data Source
AI summary
Various implementations disclosed herein include devices, systems, and methods that select colors for visual markers that include colored markings encoding data. In some implementations, the colors are automatically or semi-automatically selected. In some implementations, the colors are selected to remain sufficiently detectable despite changes in lighting conditions or printing/display conditions. In some implementations, a set of colors selectable for use in a visual marker is obtained. Then, measures of distance between a plurality of colors of the set of colors is determined, and a subset of the set of colors for the visual marker is selected based on the measure of distance between colors of the subset of colors. In some implementations, the visual marker appearance includes graphical elements encoding data using the subset of colors. In some implementations, input is received using a GUI on a display to determine multiple colors based on a source image.