classify_pixels {pixelclasser}

Classifies the pixels of an image

Description

Classifies the pixels represented in an object of class "pixel_transformed_image" using the rules contained in a list of objects of class "pixel_category".

Usage

classify_pixels(image_prop, ..., unclassed_colour = "black", verbose = TRUE)

is.classified_image(x)

## S3 method for class 'pixel_classified_image'
summary(object, ...)

Arguments

image_prop

an object of class "pixel_transformed_image" created by function read_image().

...

in classify_pixels() a list of objects of class "pixel_category"; in summary(), additional parameters (none needed by now).

unclassed_colour

a character string defining the colour of the unclassified pixels. Defaults to "black".

verbose

a logical value. When TRUE (default) the function prints some statistics about the classification.

x

the R object being tested.

object

an object of class "pixel_classified_image".

Details

This function uses the rules contained in "pixel_category" objects to create a set of incidence matrices indicating whether a pixel belongs to a pixel category or not.

To create the incidence matrices for each category, a matrix for each rule is created and then combined with the matrices of the other using the and operator. An additional matrix identifies the pixels that do not belong to the defined categories, i.e. unclassed pixels. It is always present and named unclassified even in the case that all pixels were assigned to some class.

When a category is divided in a set of subcategories the pixels are classfied in subcategories as explained in the previous paragraph, and then the matrices of the subcategories are combined again, this time using the or operator. See "pixel_subcategory" for more details.

unclassed_colour can be specified in any form understood by grDevices::col2grb.

Value

Returns an object of class "pixel_classified_image", which is a list containing nested lists. Each first-level element corresponds to one of the pixel categories and its name is the category name. They contains the second-level list, which have the following elements:

• colour: a matrix defining a colour to paint the pixels in the classified image. Inherited from the "pixel_class" object defining the class.

• incid_mat: a logical matrix where TRUE values indicate that the pixel belongs to this pixel category.

See Also

pixel_category, col2rgb.

Examples

# These are the steps to classify an example image supplied in the package

yellow <- "#ffcd0eff"
blue <- "#5536ffff"

ivy_oak_rgb <- read_image(system.file("extdata", "IvyOak400x300.JPG",
                          package = "pixelclasser"))

rule_01 <- pixel_rule("rule_01", "g", "b",
                       list(c(0.345, 1/3), c(0.40, 0.10)), comp_op = "<")
rule_02 <- pixel_rule("rule_02", "g", "b",
                       list(c(0.345, 1/3), c(0.40, 0.10)), comp_op = ">=")

cat_dead_leaves <- pixel_category("dead_leaves", blue, rule_01)
cat_living_leaves <- pixel_category("living_leaves", yellow, rule_02)

ivy_oak_classified <- classify_pixels(ivy_oak_rgb, cat_dead_leaves,
                        cat_living_leaves)