Felipe Santibañez-Leal

Felipe Santibañez-Leal

he/him

I&F Decision Science Assoc. Manager @ Accenture | Applied Scientific Researcher

ISO 4287 on Mineral Surfaces

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ISO 4287 on mineral surfaces

Implemented the standard surface roughness metrics (ISO 4287) for the depth profiler. These are the same parameters used in precision manufacturing to characterize machined surfaces — now applied to mineral samples to quantify particle size and texture.

ISO 4287 roughness parameters:
Ra = (1/N) Σ |zi - z̄| — arithmetic mean deviation
Rq = √((1/N) Σ (zi - z̄)²) — root mean square roughness
Rz = max(peaks) - min(valleys) — maximum height
Rsk = (1/N·Rq³) Σ (zi - z̄)³ — skewness (asymmetry)
Rku = (1/N·Rq⁴) Σ (zi - z̄)⁴ — kurtosis (peakedness)

The interesting finding: Ra and Rq correlate well with the coarser size fractions from sieve analysis, but for fine particles the relationship breaks down because the depth camera resolution becomes a limiting factor. We need sub-millimeter depth accuracy for the finer fractions, and the current setup gives us about 0.5mm — fine for coarse characterization but not for complete granulometry replacement.

Also added cross-section profile extraction — draw a line on the depth map and get a 1D height profile with bilinear interpolation. This is surprisingly useful for identifying particle boundaries and measuring individual grain sizes.

The Gaussian curvature analysis K = (f_xx · f_yy - f_xy²) / (1+fx²+fy²)² helps identify flat regions (K≈0, bulk material), convex peaks (K>0, particle tops), and saddle points (K<0, particle boundaries). This topological classification could feed directly into an automated particle counter.

3D Distance Profiler architecture

3D Distance Profiler on GitHub.

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