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Export multiple objects from an image to multiple images

Source: R/utils_objects.R
object_export.Rd

Givin an image with multiple objects, object_export() will split the objects into a list of objects using object_split() and then export them to multiple images into the current working directory (or a subfolder). Batch processing is performed by declaring a file name pattern that matches the images within the working directory.

Usage

object_export(
  img,
  pattern = NULL,
  dir_original = NULL,
  dir_processed = NULL,
  format = ".jpg",
  squarize = FALSE,
  augment = FALSE,
  times = 12,
  index = "NB",
  lower_size = NULL,
  watershed = FALSE,
  invert = FALSE,
  fill_hull = FALSE,
  opening = 3,
  closing = FALSE,
  filter = FALSE,
  erode = FALSE,
  dilate = FALSE,
  threshold = "Otsu",
  extension = NULL,
  tolerance = NULL,
  object_size = "medium",
  edge = 20,
  remove_bg = FALSE,
  parallel = FALSE,
  verbose = TRUE
)

Arguments

img

The image to be analyzed.

pattern

A pattern of file name used to identify images to be processed. For example, if pattern = "im" all images in the current working directory that the name matches the pattern (e.g., img1.-, image1.-, im2.-) will be imported and processed. Providing any number as pattern (e.g., pattern = "1") will select images that are named as 1.-, 2.-, and so on. An error will be returned if the pattern matches any file that is not supported (e.g., img1.pdf).

dir_original

The directory containing the original images. Defaults to NULL. It can be either a full path, e.g., "C:/Desktop/imgs", or a subfolder within the current working directory, e.g., "/imgs".

dir_processed

Optional character string indicating a subfolder within the current working directory to save the image(s). If the folder doesn't exist, it will be created.

format

The format of image to be exported.

squarize

Squarizes the image before the exportation? If TRUE, image_square() will be called internally.

augment

A logical indicating if exported objects should be augmented using image_augment(). Defaults to FALSE.

times

The number of times to rotate the image.

index

A character value specifying the target mode for conversion to binary image when foreground and background are not declared. Defaults to "NB" (normalized blue). See image_index() for more details. User can also calculate your own index using the bands names, e.g. index = "R+B/G"

lower_size

Plant images often contain dirt and dust. To prevent dust from affecting the image analysis, objects with lesser than 10% of the mean of all objects are removed. Set lower_limit = 0 to keep all the objects.

watershed

If TRUE (default) performs watershed-based object detection. This will detect objects even when they are touching one other. If FALSE, all pixels for each connected set of foreground pixels are set to a unique object. This is faster but is not able to segment touching objects.

invert

Inverts the binary image if desired. This is useful to process images with a black background. Defaults to FALSE. If reference = TRUE is use, invert can be declared as a logical vector of length 2 (eg., invert = c(FALSE, TRUE). In this case, the segmentation of objects and reference from the foreground using back_fore_index is performed using the default (not inverted), and the segmentation of objects from the reference is performed by inverting the selection (selecting pixels higher than the threshold).

fill_hull

Fill holes in the binary image? Defaults to FALSE. This is useful to fill holes in objects that have portions with a color similar to the background. IMPORTANT: Objects touching each other can be combined into one single object, which may underestimate the number of objects in an image.

opening, closing, filter, erode, dilate

Morphological operations (brush size)

  • dilate puts the mask over every background pixel, and sets it to foreground if any of the pixels covered by the mask is from the foreground.

  • erode puts the mask over every foreground pixel, and sets it to background if any of the pixels covered by the mask is from the background.

  • opening performs an erosion followed by a dilation. This helps to remove small objects while preserving the shape and size of larger objects.

  • closing performs a dilatation followed by an erosion. This helps to fill small holes while preserving the shape and size of larger objects.

  • filter performs median filtering in the binary image. Provide a positive integer > 1 to indicate the size of the median filtering. Higher values are more efficient to remove noise in the background but can dramatically impact the perimeter of objects, mainly for irregular perimeters such as leaves with serrated edges.

threshold

The theshold method to be used.

  • By default (threshold = "Otsu"), a threshold value based on Otsu's method is used to reduce the grayscale image to a binary image. If a numeric value is informed, this value will be used as a threshold.

  • If threshold = "adaptive", adaptive thresholding (Shafait et al. 2008) is used, and will depend on the k and windowsize arguments.

  • If any non-numeric value different than "Otsu" and "adaptive" is used, an iterative section will allow you to choose the threshold based on a raster plot showing pixel intensity of the index.

extension

Radius of the neighborhood in pixels for the detection of neighboring objects. Higher value smooths out small objects.

tolerance

The minimum height of the object in the units of image intensity between its highest point (seed) and the point where it contacts another object (checked for every contact pixel). If the height is smaller than the tolerance, the object will be combined with one of its neighbors, which is the highest.

object_size

The size of the object. Used to automatically set up tolerance and extension parameters. One of the following. "small" (e.g, wheat grains), "medium" (e.g, soybean grains), "large"(e.g, peanut grains), and "elarge" (e.g, soybean pods)`.

edge

The number of pixels to be added in the edge of the segmented object. Defaults to 5.

remove_bg

If TRUE, the pixels that are not part of objects are converted to white.

parallel

If TRUE processes the images asynchronously (in parallel) in separate R sessions running in the background on the same machine. It may speed up the processing time, especially when pattern is used is informed. When object_index is informed, multiple sections will be used to extract the RGB values for each object in the image. This may significantly speed up processing time when an image has lots of objects (say >1000).

verbose

If TRUE (default) a summary is shown in the console.

Value

A NULL object.

Examples

if (interactive() && requireNamespace("EBImage")) {
library(pliman)
img <- image_pliman("potato_leaves.jpg")
object_export(img,
              remove_bg = TRUE)
}