Binary Image Thinning Algorithms • thinr

Binary image thinning (skeletonization) algorithms for R. Designed as a drop-in replacement for EBImage::thinImage() with additional algorithms behind a single dispatching function.

Installation

# Once on CRAN:
# install.packages("thinr")

# From GitHub:
# install.packages("remotes")
remotes::install_github("humanpred/thinr")

Usage

library(thinr)

m <- matrix(0L, 11, 11)
m[3:9, 3:9] <- 1L      # 7x7 solid square

# Default: Zhang-Suen (matches EBImage::thinImage)
thin(m)

# Or pick an algorithm explicitly
thin(m, method = "guo_hall")

# Drop-in for EBImage::thinImage()
thinImage(m)

Algorithms

Method	Status (v0.2)	Notes
`zhang_suen`	Full	Default; matches `EBImage::thinImage()`.
`guo_hall`	Full	Slightly better diagonal-corner preservation.
`lee`	Full (2-D)	Four directional sub-iterations; crossing-number Euler-invariance.
`k3m`	Full	Six-phase lookup-table thinning; strongest corner preservation.

See vignette("choosing-a-method") for guidance.

License

LGPL-3. Chosen for drop-in compatibility with EBImage (which is LGPL) so that EBImage can optionally depend on thinr and retire its in-tree thinning code.