Pixel-Based Ratio Measurement with the GRM Model

This application proposal introduces a GRM-based method for recognizing and validating enclosed geometric shapes through direct pixel ratio measurement. The core idea is simple: in digital environments, geometry does not need to start from abstract constants or inferred parameters. It can start from what the system actually observes: pixels.

By interpreting proportional occupancy within a bounding square, GRM enables a form of pixel-native geometry that is both scalable and explainable. This makes the approach particularly suited for AI systems and imaging workflows where interpretability and robustness matter.

The document includes:

why π-based geometry is structurally misaligned with pixel grids
how GRM reframes measurement as proportional structure
a proposed implementation architecture (processing, classification, validation)
application scenarios in medical imaging, industrial inspection, education, and computer vision
practical considerations for integrating the method into existing digital pipelines

This proposal builds on the GRM whitepaper and translates its proportional logic into a practical foundation for pixel-based digital measurement and shape interpretation.

Published: v1.1 | May 17, 2025 | Language: English | Pages: 21

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