Our platform combines computer vision, particle measurement, and automated classification to transform grain images into actionable sand quality data. The workflow is designed to support fast, repeatable, and scalable digital analysis.
Processing Pipeline
Each uploaded image moves through a structured digital workflow that detects grains, measures particle characteristics, and organizes results into analysis-ready outputs.
AI Grain Detection
Individual sand grains are identified from uploaded images using computer vision and contour-based segmentation. This allows the platform to isolate particle boundaries from the background.
Particle Size Measurement
Each detected grain is measured digitally to estimate particle size and classify material into sieve-related ranges. This creates a repeatable and scalable alternative to manual inspection.
Roundness & Sphericity
The system evaluates grain shape characteristics from particle contours to estimate roundness and sphericity. These metrics support deeper quality assessment beyond size alone.
Virtual Sieve Classification
Measured particles are grouped into sieve-style categories to generate a digital size distribution. This helps transform grain images into practical laboratory-style outputs.
Fast Batch Processing
Multiple images can be processed in one workflow, making the platform suitable for high-throughput analysis. The pipeline is designed for speed, repeatability, and future industrial scaling.
Reporting & Visualization
Outputs are transformed into clean visual summaries such as particle size distributions, classification charts, and analysis-ready data views for technical review.