Martin Coath edited section_Methods_subsection_Algorithm_For__.tex  about 8 years ago

Commit id: 2a5c40d0a7f7b9c32bff3c0adcc55b66ad1e5a42

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For results derived from monochrome images each pixel is defined by three values; two coordinates $i$ and $j$, and a single value $k$ that is the value of the pixel on the gray-scale from 0 (black) to 1 (white). Images are processed on a pixel-by-pixel basis and the \textsc{skv} value of each pixel $\gamma_{i,j}$ is calculated thus:  \begin{enumerate}  \item the number of pixels $m$ corresponding to half the required window size $w$ is calculated: $m = \mathrm{floor}(\frac{w}{2})$  \item hence the working window size $n$ is always odd and equal to  $2m+1$ even when this differs from $w$ by one \item assemble the horizontal vector $\vec{k}_{h}$ of values for a window of $n$ pixels $k_{[i,j-m \: : \: i,j+m]}$  \item repeat with $\vec{k}_{v}$, a vector of values for a vertical window of $n$ pixels $k_{[i-m,j \: : \: i+m,j]}$  \item both vectors are normalized, so they can be treated as distributions, and the skewness of each distribution (\textit{i.e.} a measure of the asymmetry in the gray-scale values in both direction) is calculated, $\gamma_h$ and $\gamma_v$