Image Pattern Decoding Using Pixel Subsets for Data Tagging
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Solution Overview
Problem
Existing methods for encoding and decoding digital identifiers on physical objects are inefficient in terms of surface area usage and robustness, often distracting from the object's primary purpose and struggling with low-resolution image processing.
Innovation Solution
A method and system for decoding an image pattern on an object by associating specific subsets of pixels with a sub-image and data tag, using a processor to determine digital identifiers and tag values, allowing for efficient data encoding and robust decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If patterns are displayed on physical objects to represent digital data, then digital identification is enabled, but the patterns occupy dedicated surface area that cannot be used for other displays and may distract from the physical object
Solution Approach 1:
The pattern is segmented into multiple functional components: a first portion containing the digital identifier and a second portion containing data values. This segmentation allows different types of information to be encoded in distinct regions, improving decoding efficiency while maintaining compact surface area usage.
Solution Approach 2:
Different portions of the pattern are assigned different functional qualities - the first portion is optimized for digital identification while the second portion encodes additional data values. This local differentiation enables efficient use of surface area by giving each region a specific purpose rather than using the entire pattern for a single function.
2Reliability
If two-dimensional marketing materials are photographed as low resolution images, then data can be transmitted to the user, but the processing of the two-dimensional graphic may not be sufficiently robust to recognize its identity in commercial application
Solution Approach 1:
The pattern is designed with built-in structural features and redundancy before the imaging process occurs. The segmented structure with distinct functional portions and the inclusion of multiple data representation methods prepare the pattern to withstand low-resolution imaging and processing, enabling robust recognition even when captured by standard digital cameras.
Solution Approach 2:
The system accommodates variations in image resolution by using multiple data encoding approaches and redundancy. The pattern can be decoded from low-resolution images by leveraging the structured organization of data portions and the ability to retrieve information through different decoding paths, making the system resilient to resolution parameter changes.
Data Source
AI summary
A method is provided for decoding an image of a pattern associated with an object to determine a digital identifier and to obtain data. The method comprises receiving a image of a pattern associated with the object. The pattern comprises a sub-image and a data tag. The image comprising a plurality of pixels. The method further comprises associating a first sub-set of the pixels with the sub-image and a second sub-set of the pixels with the data tag, determining a digital identifier of the sub-image based on the first sub-set of the pixels, and determining a tag value of the data tag based on the second sub-set of the pixels.