image_surf: Find SURF points in an image

In image.dlib: Image Processing Functionality using the 'dlib' Package

Find SURF points in an image

Description

SURF (speeded up robust features) points are blobs in a digital image https://en.wikipedia.org/wiki/Speeded_up_robust_features. The function identifies these points in the image and also provides a numeric descriptor of each point.

This SURF descriptor is used on computer vision applications like object matching (by comparing the SURF descriptor of several images using e.g. kNN - from the rflann package) or object recognition. The SURF feature descriptor is based on the sum of the Haar wavelet response around the point of interest. More information on the calculation, see the reference paper.

Usage

image_surf(x, max_points = 1000, detection_threshold = 30)

Arguments

x	a 3-dimensional array of integer pixel values where the first dimension is RGB, 2nd the width of the image and the 3rd the height of the image. See the example.
max_points	maximum number of surf points to find
detection_threshold	detection threshold (the higher, the lower the number of SURF points found)

Value

a list with SURF points found and the SURF descriptor. It contains:

• points: The number of SURF points

• x: The x location of each SURF point

• y: The y location of each SURF point

• angle: The angle of each SURF point

• pyramid_scale: The pyramid scale of each SURF point

• score: The score of each SURF point

• laplacian: The laplacian at each SURF point

• surf: The SURF descriptor which is a matrix with 64 columns describing the point

References

SURF: Speeded Up Robust Features By Herbert Bay, Tinne Tuytelaars, and Luc Van Gool

Examples

library(magick)
f <- system.file("extdata", "cruise_boat.png", package = "image.dlib")
x <- image_read(f)
x
surf_blobs <- image_data(x, channels = "rgb")
surf_blobs <- as.integer(surf_blobs, transpose = FALSE)
surf_blobs <- image_surf(surf_blobs, max_points = 10000, detection_threshold = 50)
str(surf_blobs)

library(magick)
plt <- image_draw(x)
points(surf_blobs$x, surf_blobs$y, col = "red", pch = 20)
dev.off()
plt
## Not run: 
## Plot the points
"as.cimg.magick-image" <- function(x){
  out <- lapply(x, FUN=function(frame){
    frame <- as.integer(frame[[1]])[, , 1:3] # dropping the alpha channel
    dim(frame) <- append(dim(frame), 1, after = 2)
    frame
  })
  out$along <- 3
  out <- do.call(abind::abind, out)
  out <- imager::as.cimg(out)
  out <- imager::permute_axes(out, "yxzc")
  out
}
library(imager)
library(magick)
library(abind)
img <- image_read(path = f)
plot(as.cimg(img), main = "SURF points")
points(surf_blobs$x, surf_blobs$y, col = "red", pch = 20)

## End(Not run)

library(magick)
img1   <- image_scale(logo, "x300")
img2   <- image_flip(img1)
height <- image_info(img1)$height
sp1 <- image_surf(image_data(img1, channels = "rgb"), max_points = 50)
sp2 <- image_surf(image_data(img2, channels = "rgb"), max_points = 50)

## Match surf points and plot matches
library(FNN)
k <- get.knnx(sp1$surf, sp2$surf, k = 1)
combined <- image_append(c(img1, img2), stack = TRUE)
plt <- image_draw(combined)
points(sp1$x, sp1$y, col = "red")
points(sp2$x, sp2$y + height, col = "blue")
for(i_from in head(order(k$nn.dist), 50)){
  i_to   <- k$nn.index[i_from]
  lines(x = c(sp1$x[i_to], sp2$x[i_from]), y = c(sp1$y[i_to], sp2$y[i_from] + height), col = "red")
}
dev.off()
plt

image.dlib documentation built on Oct. 18, 2022, 9:06 a.m.