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Morphological profiles segmentation

segm_mprofiles.Rd

Applies the morphological profiles segmentation algorithm to an image file or a SpatRaster

Usage

segm_mprofiles(
  image,
  otb,
  size = 5L,
  start = 1L,
  step = 1L,
  sigma = 1,
  mode = "vector",
  vector_neighbor = FALSE,
  vector_stitch = TRUE,
  vector_minsize = 1L,
  vector_simplify = 0.1,
  vector_tilesize = 1024L,
  mask = NULL
)

Arguments

image

path or SpatRaster

otb

output of link2GI::linkOTB()

size

integer. Size of the profiles

start

integer. Initial radius of the structuring element in pixels

step

integer. Radius step in pixels along the profile

sigma

profiles values under the threshold will be ignored

mode

processing mode, either 'vector' or 'raster'. See details

vector_neighbor

logical. If FALSE (the default) a 4-neighborhood connectivity is activated. If TRUE, a 8-neighborhood connectivity is used

vector_stitch

logical. If TRUE (the default), scans polygons on each side of tiles and stitch polygons which connect by more than one pixel

vector_minsize

integer. Objects whose size in pixels is below the minimum object size will be ignored during vectorization

vector_simplify

simplify polygons according to a given tolerance (in pixel). This option allows reducing the size of the output file or database.

vector_tilesize

integer. User defined tiles size for tile-based segmentation. Optimal tile size is selected according to available RAM if NULL

mask

an optional raster used for masking the segmentation. Only pixels whose mask is strictly positive will be segmented

Value

sf or SpatRaster

Details

The morphological profiles segmentation algorithm is a region-based image segmentation technique that applies a series of morphological operations using structuring elements of increasing size to capture spatial patterns and textures within the image. Steps:

  1. Morphological Filtering: The algorithm applies a sequence of openings (removing small bright structures) and closings (removing small dark structures) to the input image using structuring elements (e.g., disks, rectangles).

  2. Profile Generation: It generates a profile for each pixel by recording the response of the morphological operations at different scales.

  3. Feature Extraction: These profiles help capture both fine and coarse structures within the image, creating a set of features that can be used for classification or segmentation.

  4. Segmentation (Optional): The extracted profiles can be input into a classifier or segmentation algorithm to differentiate between regions with distinct spatial characteristics.

The processing mode 'vector' will output a vector file, and process the input image piecewise. This allows performing segmentation of very large images. IN contrast, 'raster' mode will output a labeled raster, and it cannot handle large data. If mode is 'raster', all the 'vector_*' arguments are ignored.

Examples

if (FALSE) { # \dontrun{
## load packages
library(link2GI)
library(OTBsegm)
library(terra)

## load sample image
image_sr <- rast(system.file("raster/pnoa.tiff", package = "OTBsegm"))

## connect to OTB (change to your directory)
otblink <- link2GI::linkOTB(searchLocation = "C:/OTB/")

## apply segmentation
results_ms_sf <- segm_mprofiles(
    image = image_sr,
    otb   = otblink,
    size  = 5,
    start = 3,
    step  = 20,
    sigma = 1
)
} # }