Imperfect Surface Patterns for Aesthetic Machine-Readable Encoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing machine-readable optical codes, such as barcodes and digital watermarks, are ineffective in communicating emotional or cultural framing and are difficult to scan under varied conditions, especially when objects are moving, out of focus, or have imperfect lighting, and they detract from the aesthetic appeal of the object they are applied to.
Innovation Solution
The use of 'imperfect patterns' that incorporate intentional design variations to encode data, which can be decoded using machine learning models, allowing for robust data extraction from images of objects with curved or partially obscured surfaces, even under challenging conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional machine-readable optical codes are used, then data encoding capability is achieved, but aesthetic appeal and emotional framing are compromised
Solution Approach 1:
The patent merges traditional machine-readable code functionality with artistic graphic design elements into a unified visual composition. The code is not separate from the design but integrated within it, allowing both data encoding and aesthetic expression to coexist in the same visual space.
Solution Approach 2:
The visual artifacts serve multiple functions simultaneously: they encode data for machine reading, convey emotional or cultural framing for human perception, and maintain aesthetic appeal as design elements. This multi-functionality resolves the contradiction by making the code system universally applicable to both technical and artistic requirements.
2Area of stationary object
If codes are made small for most applications, then space efficiency is improved, but scanning difficulty increases
Solution Approach 1:
The system dynamically adapts the size and complexity of visual artifacts based on application requirements. Rather than using fixed small codes, the artifacts can scale and transform to optimize both space utilization and scan detectability for different contexts.
Solution Approach 2:
The patent changes key parameters of the visual artifacts including size, contrast, shape, and spatial distribution to optimize the balance between compactness and scan detectability. These parameter adjustments allow the same encoding system to work effectively at various scales.
3Reliability
If digital watermarks are added to brand logos, then data encoding is achieved, but aesthetic quality and brand messaging are degraded
Solution Approach 1:
The patent applies different levels and types of visual artifact encoding to different regions or elements within the overall design. Rather than uniformly degrading the entire logo, the encoding is localized to specific areas, preserving the aesthetic quality and emotional impact of critical brand elements while still achieving data encoding functionality.
4Productivity
If existing codes are used under varied lighting and motion conditions, then data transmission is attempted, but detection reliability deteriorates
Solution Approach 1:
The system incorporates error correction and robustness features in advance during the encoding phase. Visual artifacts are designed with built-in redundancy and tolerance to anticipated distortions from lighting changes, motion blur, and focus issues, cushioning against detection failures before they occur.
Data Source
AI summary
Embodiments of the invention include ascribing a predetermined data record to a physical surface in the form of an imperfect aesthetic pattern of marks. An image showing a portion of the surface, when processed with a decoder, yields the predetermined, verified data record.