edgecluster {edci} | R Documentation |
edgecluster
is a simple combination of edgepoints
and oregMclust
. It just passes the results of
edgepoints
to oregMclust
.
edgecluster(data, h1n, h2n, maxval, bw = max(h1n, h2n)/qnorm(0.975), asteps = 4, estimator = "M_median", kernel = "gauss", score = "gauss", sigma = 1, kernelfunc = NULL)
data |
See description of |
h1n, h2n |
See description of |
asteps |
See description of |
estimator |
See description of |
kernel |
See description of |
score |
See description of |
sigma |
See description of |
kernelfunc |
See description of |
maxval |
See description of |
bw |
See description of |
A list of two numerical matrices. The first matrix
contains the results of oregMclust
, which are the
'edgeclusters'. The second matrix contains the result of
edgepoints
.
Tim Garlipp, TimGarlipp@gmx.de
edgepoints
, oregMclust
,
eplist
# generate a 60x60 zero matrix y = matrix(rep(0, 60 * 60), nrow = 60) # set a square-shaped set of elements to 1 y[21:40, 21:40] = 1 # add some noise y = y + matrix(rnorm(60 * 60, 0, 0.2), nrow = 60) # plot it image(y, col = gray(seq(0, 1, 1/255))) # find edge points of the square-shaped object ec = edgecluster(y, 0.05, 0.05, 0.7, estimator = "M_median", kernel = "gauss") plot(bestMclust(ec[[1]], 4), ec[[2]], xlim = c(0, 1), ylim = c(0, 1))