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  "Title": "Binary Image Thinning Algorithms",
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  "Authors@R": "person(\"Bill\", \"Denney\", , \"wdenney@humanpredictions.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-5759-428X\",\naffiliation = \"Human Predictions, LLC\"))",
  "Description": "Thinning (skeletonization) algorithms for binary raster\nimages. Provides seven algorithms behind a single dispatching\nfunction: Zhang-Suen (Zhang and Suen 1984)\n<doi:10.1145/357994.358023>, Guo-Hall (Guo and Hall 1989)\n<doi:10.1145/62065.62074>, a 2-D adaptation of Lee (Lee,\nKashyap, and Chu 1994) <doi:10.1006/cgip.1994.1042>, K3M\n(Saeed, Tabedzki, Rybnik, and Adamski 2010)\n<doi:10.2478/v10006-010-0024-4>, the parallel form commonly\nattributed to Hilditch (1969, in 'Machine Intelligence 4'),\nOPTA / SPTA (Naccache and Shinghal 1984), and Holt and\ncolleagues (1987) <doi:10.1145/12527.12531>. Also provides the\nmedial axis transform (Blum 1967) and a distance transform\nimplementation following Felzenszwalb and Huttenlocher (2012)\n<doi:10.4086/toc.2012.v008a019>. The drop-in thinImage()\nmatches the signature of thinImage() in the 'EBImage' package\non Bioconductor so existing code can switch parsers without\nchanges. The wider thin() API selects the algorithm by name.",
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  "BugReports": "https://github.com/humanpred/thinr/issues",
  "Repository": "https://humanpred.r-universe.dev",
  "Date/Publication": "2026-06-29 01:54:11 UTC",
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