hole_columm {bwimage}

Holes description in columns sections

Description

Summary information of holes in a given number of columns (n_sections). n_sections must be set as a number, in this situation hole_columm will sample columns, and apply hole_section_data function for each section. Next, all results will be display on hole_columm output. Example of how column sample works: in a matrix of 250x250 if n_sections = 5 , it will sample columns 1,51,101,151, and 201 and analyze it. In other words, the sections will be following sections of the original matrix [1:250,1] , [1:250,51], [1:250,101], [1:250,151], [1:250,201]. The default for parameter n_sections is "all", it will calculate hole_section_data for each column of pixel. In other words, it will break the image in a number of section equal to the image pixel width.

Usage

hole_columm(imagematrix, color = 0, n_sections = "all")

Arguments

imagematrix

The matrix to be analysed.

color

Color of the hole (0 or 1).

n_sections

Sample this number of columns.

Value

N

Number of sections.

Mean

Mean sections size.

SD

standard deviations of sections size.

Min

Minimum sections size sections size.

Max

Maximum sections size.

LH

Stratum with largest hole count.

Author(s)

Carlos Biagolini-Jr.

References

Zehm et al 2003 Multiparameter analysis of vertical vegetation structure based on digital image processing. Flora-Morphology, Distribution, Functional Ecology of Plants, 198: 142-160.

See Also

hole_section_data threshold_color

Examples

# First, get a matrix from your image. Here an example of a bush image is used.
bush<-system.file("extdata/bush.JPG",package ="bwimage")
bush_imagematrix<-threshold_color(bush,  "jpeg",  "proportional", compress_rate = 0.1)

# Information of white (i.e. 0s in matrix) holes in 5 columns uniformly sample among matrix.
hole_columm(bush_imagematrix, n_sections=5 )

# Information of black (i.e. 1s in matrix) holes in 20 columns uniformly sample among matrix.
hole_columm(bush_imagematrix, n_sections=20 )