radsym 0.1.3

Radial symmetry detection: center proposals, local support analysis, scoring, and refinement
Documentation

radsym

radsym is a Rust library for radial symmetry detection: center proposal generation, local circular and elliptical support analysis, support scoring, and local image-space refinement.

The crate is CPU-first, deterministic, and composable. You can use proposal generation, scoring, and refinement independently instead of committing to a single end-to-end pipeline.

Installation

[dependencies]
radsym = "0.1"

Quick start

use radsym::{
    ImageView, FrstConfig, Circle, Polarity, ScoringConfig, NmsConfig,
    sobel_gradient, frst_response, extract_proposals, score_circle_support,
};

let size = 64;
let mut data = vec![0u8; size * size];
for y in 0..size {
    for x in 0..size {
        let dx = x as f32 - 32.0;
        let dy = y as f32 - 32.0;
        if (dx * dx + dy * dy).sqrt() <= 10.0 {
            data[y * size + x] = 255;
        }
    }
}

let image = ImageView::from_slice(&data, size, size).unwrap();
let gradient = sobel_gradient(&image).unwrap();

let config = FrstConfig { radii: vec![9, 10, 11], ..FrstConfig::default() };
let response = frst_response(&gradient, &config).unwrap();

let nms = NmsConfig { radius: 5, threshold: 0.0, max_detections: 5 };
let proposals = extract_proposals(&response, &nms, Polarity::Bright);

if let Some(best) = proposals.first() {
    let circle = Circle::new(best.seed.position, 10.0);
    let score = score_circle_support(&gradient, &circle, &ScoringConfig::default());
    assert!(score.total > 0.0);
}

Modules

  • core: image views, geometry, gradients, NMS, errors
  • propose: FRST, RSD, proposal extraction, homography-aware proposal tools
  • support: annulus sampling, evidence extraction, support scoring
  • refine: radial center, circle refinement, ellipse refinement
  • diagnostics: response heatmaps and overlays
  • affine: experimental affine-aware extensions behind the affine feature

Feature flags

  • rayon: parallel multi-radius proposal computation
  • image-io: PNG and JPEG image loading via image
  • tracing: structured instrumentation
  • affine: experimental affine-aware extensions
  • serde: serialization for configs and results

Conventions

  • Coordinates use (x=col, y=row) everywhere.
  • Pixel-level computation uses f32.
  • ImageView<'a, T> is the core borrowed image abstraction.

References

  • FRST: Loy and Zelinsky, IEEE TPAMI 2003
  • RSD: Barnes, Zelinsky, Fletcher, IEEE T-ITS 2008
  • Radial center: Parthasarathy, Nature Methods 2012
  • GFRS: Ni, Singh, Bahlmann, CVPR 2012

License

Licensed under MIT OR Apache-2.0.