segment_image_mser — 2D `segmentation` op

• Data kinds: image → region

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

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

Usage

MSER (Maximally Stable Extremal Regions) detection (`cv2.MSER_create). Detects regions whose shape remains stable even as the threshold is continuously varied, and returns their boundaries (used for detecting regions such as text and logos robustly against illumination changes). Corresponds to HALCON's segment_image_mser` (Segment image using Maximally Stable Extremal Regions (MSER).).

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

`a が MSER の安定性パラメータ(delta、3〜11)を振る。b` は未使用。

`cv2` が無い環境ではこの分岐は呼べない。

Detailed usage guide

• gallery2d_segmentation 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_segmentation — py -3.11 examples/gallery2d_segmentation.py

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

identity · reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small

Same category (`segmentation`)

threshold · otsu · canny · adaptive_gauss_thresh · sk_otsu · sk_li · sk_yen · sk_sauvola

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

segment_image_mser — 2D segmentation op