dKQ: edge detection, performance measure

In DRIP: Discontinuous Regression and Image Processing

edge detection, performance measure

Description

Compute the d_KQ distance between two sets of edge pixels. It can be used as a performance measure for (step/roof) edge detectors

Usage

dKQ(edge1, edge2)

Arguments

edge1	One set of pixels
edge2	The other set of pixels

Details

The mathematical definition of d_{KQ} is as follows. d_{KQ}(S_1, S_2) = \frac{0.5}{|S_1|}\sum_{p_1\in S_1} d_E(p_1, S_2) + \frac{0.5}{|S_2|}\sum_{p_2\in S_2} d_E(p_2, S_1), where S_1 and S_2 are two point sets, and d_E denotes the Euclidean distance.

Value

Value of the d_{KQ}

References

Kang, Y., and Qiu, P., "Jump Detection in Blurred Regression Surfaces," Technometrics, 56, 2014, 539-550.

Examples

mat1 <- matrix(c(1, rep(0, 3)), ncol = 2)
mat2 <- matrix(c(rep(0, 3), 1), ncol = 2)
dKQ(mat1, mat2)

DRIP documentation built on Sept. 1, 2023, 5:08 p.m.