PoreSizer™ Image Analysis
Particle sizing from micrographs — flood fill, scale calibration, ISO 13322.
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Theory & method
PoreSizer performs static image analysis of a single micrograph following ISO 13322-1:2014. Dark features (particles or pores) are separated from the background by a grayscale threshold, and each connected region is measured by its equivalent circular diameter — the diameter of a circle with the same projected area, x_A = √(4A/π), also called the Heywood or area-equivalent diameter (ISO 13322-1 §3.1.1, ISO 9276-6).
Segmentation converts the image to grayscale as (R+G+B)/3 (the unweighted mean, matching ImageJ's default) and marks every pixel darker than the threshold as belonging to a particle; connected pixels are grouped by an iterative flood fill (8-connected by default, matching ImageJ/OpenCV/scikit-image). The Auto button sets the threshold by Otsu's method (1979), which maximizes the between-class variance σ²_B = ω₀ω₁(μ₀−μ₁)² of the luminance histogram.
Particles cut by the edge of the measurement frame bias the size distribution, because a large particle is more likely to touch the border than a small one. ISO 13322-1 §8.3 corrects this with the Miles-Lantuéjoul factor: border-touching particles are excluded from measurement and each retained particle is weighted by 1/P_i, with P_i = (Z₁−w)(Z₂−h)/(Z₁·Z₂) the probability that a particle of that bounding size fits inside the frame. PoreSizer applies this by default; you can also simply exclude or include border particles.
Results can be reported by number (Q₀) or by projected area (Q₂), the quantity type r of ISO 9276-1. Image analysis is inherently number-based; the area weighting is a two-dimensional proxy in which larger particles carry more weight, not a true mass or volume distribution — converting to volume (Q₃) would require a stereological shape assumption to infer 3D volume from a 2D projection, which this tool does not make. Report the quantity type with every statistic.
The reliability of a percentile depends on how many particles were measured: the median x₅₀ is the most robust, while the tails (x₁₀, x₉₀) and area/volume weighting need far more particles — thousands for a dependable x₉₀ (ISO 13322-1 Annex A; Masuda & Iinoya 1971). Digitization also limits accuracy: below roughly 10 pixels in diameter the pixel-count area error grows quickly, so PoreSizer flags particles that small. Everything runs locally in your browser; your images never leave your device.
How to use
- 01Upload a micrograph by dragging it onto the canvas, pasting from the clipboard, or browsing. Decoding and analysis happen entirely in your browser.
- 02Calibrate the scale so results are in physical units: with the Reference-object method, switch to the measure tool, draw a line across a feature of known size, click "Use line" and enter the real size; or with the Microscope method, enter the camera sensor pixel size and the total magnification.
- 03Optionally use the region tool to draw one or more areas of interest — this excludes scale bars, labels or artifacts from the analysis (hold Shift to add several regions).
- 04Set the grayscale threshold while watching the binarization mask highlight exactly what will be measured, or click Auto (Otsu). Under Advanced, tune the minimum particle size, 4/8 connectivity, hole filling, and how edge particles are handled (Miles-Lantuéjoul by default).
- 05Click Analyze to read the particle count, mean diameter, D10/D50/D90, coverage and the sieve granulometry chart; switch between Q₀ (count) and Q₂ (area) weighting, and open the full particle table.
- 06Export a CSV with the complete data — parameters, aggregates, both granulometries and every particle — or a formatted PDF report with the distribution chart.
Frequently asked questions
Why do image-analysis results differ from sieving?
Image analysis measures the projected two-dimensional size of the features visible in one image and reports a number-based distribution, while sieving sorts three-dimensional particles by how they pass apertures and is mass-based. A handful of large particles dominate a mass distribution but count for little by number, so the two methods legitimately give different numbers; they are complementary, not interchangeable.
Why are touching particles counted as one?
Flood-fill segmentation cannot separate particles that physically touch, and ISO 13322-1 requires measurements on isolated particles. Separation by watershed is not included in this version — reduce the particle density on the slide, or draw regions around well-separated particles, to get reliable counts.
Does PoreSizer measure pores or particles?
It segments dark regions, which may be particles or pores, and reports their projected 2D size — a surface, image-based measurement in the spirit of ISO 13322-1. This differs from and complements fluid-flow porometry such as ASTM F316 (bubble point / mean-flow pore) and ASTM D6767 (capillary flow for geotextiles), which report the narrowest through-pore constriction that controls flow rather than the projected opening.
Can I upload HEIC photos?
Safari 17 and later decode HEIC natively; Chrome and Firefox do not, so convert HEIC/AVIF to JPG or PNG first. Microscopy sources normally export TIFF or PNG, which are fully supported.
How many particles do I need?
The median (x₅₀) is reliable with relatively few particles, but high percentiles such as x₉₀ and area/volume weighting need far more — often thousands (ISO 13322-1 Annex A; Masuda & Iinoya 1971). PoreSizer warns you when the count is low relative to the statistics you are reading.
Normative references
- ISO 13322-1:2014 — Particle size analysis — Image analysis methods — Part 1: Static image analysis methods.
- ISO 9276-1 — Representation of results of particle size analysis — Part 1: Graphical representation.
- ISO 9276-6:2008 — Representation of results of particle size analysis — Part 6: Descriptive and quantitative representation of particle shape and morphology.
- N. Otsu (1979). A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems, Man, and Cybernetics 9(1): 62–66.
- R. E. Miles (1974) and C. Lantuéjoul (1980) — correction of edge effects in the analysis of individual particles in a planar frame.
- T. Allen (1997). Particle Size Measurement, 5th ed. Chapman & Hall — required particle counts versus precision.