Φ

—- July 2026 | Status Update —-

Major update | The phi-exe methodology for photometric surface topography mapping is now fully optimized for consumer-grade imaging hardware and a freely available open-source toolchain (R, C++).

It has been about six months since my last update. Development has slowed down since I started a new job. My original intent was to start my own grading company, but I no longer have time for that. So I’m pursuing a full transfer of the methodology to a single acquirer. Sample outputs from the current version are listed below.

The phi-exe pipeline is built on 15+ years of formal training (PhD and postdoctoral fellowship) in computational analysis of oscillatory dynamics and photometric signal processing, including first-author publication in Nature Reviews Genetics, applied to precision surface characterization of trading cards.

What transfers:

Surface scoring pipeline: Lambert photometry module, back integrity module, holographic foil (pendulum) module
Card alignment and QC tooling (Shiny-based)
HTML report generation and deployment infrastructure
Submission intake backend (Google Sheets / Apps Script)
Complete source code (R / C++)
3D scanning training and documentation
Post-transfer technical support: 30 days or 20 hours, whichever comes first

Acquisition terms:

Priced for a single commercial acquisition; price available upon inquiry
Technical details and source code disclosed only after execution of a mutual NDA
Full IP assignment available, including exclusive rights with no retained license
Transfer to one buyer only

Direct inquiries to [email protected]. I am based in Toronto, Canada.

—- About Φ —-

This is not an AI
This is not a mobile app
This is empirical scientific research

Φ is the first statistically rigorous, reproducible method for trading card condition assessment. Built on a novel proprietary scanning methodology and Lambertian reflectance physics, it measures the physical properties of card surfaces and edges. Not human judgment, and not trained AI.

Φ (photoangular harmonic index) is an objective, quantitative card condition index developed by a PhD scientist in Toronto, Canada. Traditional grading relies on human visual inspection prone to inter-rater variability, lighting conditions, and perceptual bias. Φ replaces that with empirical measurements and rigorous statistical analysis.

—- What Φ measures —-

Φ is a composite surface index derived from structured-light 3D imaging. Raw data are processed through a proprietary signal analysis pipeline to extract the following empirical measures:

Surface topography | The surface is reconstructed at micrometer resolution, enabling detection and quantification of indentations, scratches, creases, and localized deformations. Surface irregularity is expressed as a continuous deviation metric rather than a categorical descriptor.
Edge integrity | Edge profiles are extracted and assessed for angular irregularities, chipping, and wear. Because edge damage accumulates non-uniformly, each edge is scored independently before integration into the composite score.
Photometric analysis | The approach captures how surface microstructure interacts with light across the angular domain. Proprietary signal decomposition methods separate surface irregularities from intrinsic card characteristics. Holographic cards undergo additional spectral processing prior to scoring.
Centering and alignment | Border geometry is measured at approximately 0.09-0.17 mm precision, yielding left/right and top/bottom offset ratios.

—- Example Φ outputs —-

Φ.exe

Φ