blob_count — 2D `features` op

• Data kinds: region → feature

• Call: fullseye.apply(img, "blob_count", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

• HALCON equivalent: count_obj (the HALCON reference is a useful guide to its meaning and parameters)

Usage

Number of connected components in the region (HALCON count_obj).

> The detailed description below is the original text — the summary and the headings are translated.

2026-08-30: 8 連結既定に修正(HALCON パリティ — connection/計数の既定は

8 連結。従来は scipy.ndimage.label の既定 = 4 連結で、対角接触した 2 画素を

2 個と数えていた: KNOWN_ISSUES #1)。旧 4 連結は connectivity=4 で。

Detailed usage guide

• gallery2d_features family guide

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• gallery2d_features — py -3.11 examples/gallery2d_features.py

• quickstart — py -3.11 examples/quickstart.py

Ops the type connects to (they accept `feature` as input)

identity

Same category (`features`)

area_frac · count_contours · total_length · vol_count · sk_euler · sk_entropy_feat · sk_blur_effect · cv_cc_count

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

blob_count — 2D features op