Multi-Dimensional Encrypted Code Decoding With Color Patterns
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Solution Overview
Problem
Traditional data encoding methods, such as barcodes and QR codes, are limited in data capacity, vulnerable to tampering, and lack flexibility, especially in dynamic and secure data transmission scenarios, failing to cater to diverse user needs, including visually impaired users.
Innovation Solution
A method and electronic device for decoding multi-dimensional encrypted codes using color patterns, incorporating digital watermarks, error correction, machine learning, and direct access to information without intermediary servers, enabling dynamic data representation and accessibility features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional barcodes and QR codes are used for data encoding, then the decoding process is simple, but the data capacity is limited and security is vulnerable
Solution Approach 1:
The patent transitions from traditional two-dimensional QR codes to a multi-dimensional color-coded system that incorporates hue, saturation, and brightness dimensions. Each color dimension encodes additional data layers, enabling the representation of complex information such as URLs, text, and multimedia data within a single compact code structure, thereby significantly increasing data capacity without proportionally increasing code size.
Solution Approach 2:
The patent implements nested encoding by embedding multiple data layers within the color code structure. The code contains nested information including primary data, encrypted data, error correction codes, and metadata, all organized in concentric layers that can be decoded sequentially from outer to inner layers, maximizing information density within the code space.
2Reliability
If traditional barcodes and QR codes are used, then the structure is simple, but they are susceptible to unauthorized copying and tampering
Solution Approach 1:
The patent introduces digital watermarks as intermediary elements embedded within the color code structure. These watermarks serve as authentication markers that verify the legitimacy and ownership of the encoded data, preventing unauthorized copying and tampering by detecting and identifying the embedded watermark signatures during the decoding process.
Solution Approach 2:
The patent incorporates error correction codes and authentication watermarks in advance during the encoding process. These preventive measures are embedded before the code is deployed, enabling the system to detect and correct tampering attempts or provide authentication verification, thereby enhancing security against unauthorized modifications without requiring complex real-time verification systems.
3Ease of operation
If intermediary servers and URL shorteners are used for data redirection, then data management is simplified, but latency increases and privacy is compromised
Solution Approach 1:
The patent extracts and eliminates the need for intermediary servers and URL shorteners by directly embedding complete data including URLs and multimedia information within the multi-dimensional color code. The code contains self-contained information that can be decoded and accessed directly by the user's device, removing the mandatory intermediary step and enabling immediate data retrieval without routing through external servers, thereby reducing latency and preserving user privacy.
4Measurement precision
If traditional decoding mechanisms are used, then the process is straightforward, but accuracy decreases in real-world conditions with code variations
Solution Approach 1:
The patent implements feedback mechanisms through error correction codes that enable the decoding system to detect and correct variations in the color code. The decoding process incorporates iterative refinement where the system compares detected patterns against expected values and automatically adjusts interpretations based on feedback from error correction data, maintaining high accuracy even when dealing with code variations, damage, or obscured regions.
Data Source
AI summary
A method for decoding information in a multi-dimensional encrypted code is disclosed. The method involves scanning the code with an image sensor, identifying color patterns within geometrical shapes, and translating these patterns into user-readable information or URLs. The system enhances security by bypassing intermediate servers and using embedded features like digital watermarks to prevent unauthorized access. Error correction techniques ensure accurate decoding even if the code is damaged. Additionally, a neural network improves pattern recognition through machine learning. The user interface offers customization options and accessibility features, while spectral analysis distinguishes subtle color variations to encode more data. An example demonstrates decoding a product label's encrypted code into alphanumeric characters, ensuring accurate and reliable information display. This method ensures secure, flexible, and user-friendly decoding of complex encrypted information.