hole_row {bwimage} | R Documentation |
Summary information of holes in a given number of rows (n_sections). n_sections must be set as a number, in this situation hole_row will sample rows, and apply hole_section_data function for each section. Next, all results will be display on hole_columm output. Example of how row sample works: in a matrix of 250x250 if n_sections = 5 , it will sample rows 1,51,101,151, and 201 and analyze it. In other words, the sections will be following sections of the original matrix [1,1:250] , [51,1:250] , [101,1:250] , [151,1:250] , [201,1:250]. The default for parameter n_sections is "all", it will calculate hole_section_data for each row of pixel. In other words, it will break the image in a number of section equal to the image pixel height.
hole_row(imagematrix, color = 0, n_sections = "all")
imagematrix |
The matrix to be analysed. |
color |
Color of the hole (0 or 1). |
n_sections |
Sample this number of rows. |
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. |
Carlos Biagolini-Jr.
hole_section_data threshold_color
# 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 10 rows uniformly sample among matrix. hole_row(bush_imagematrix, n_sections=10) # Information of black (i.e. 1s in matrix) holes in 15 rows uniformly sample among matrix. hole_row(bush_imagematrix, n_sections=15)