Algorithm 3: Calculating the distances among the feature vectors within a digit class

$\mathrm{Assume} \mathrm{that} {\mathit{F}}^{\mathit{m}} = \left(f_1 f_2 \dots f_S\right)$$\mathrm{is} \mathrm{a} \mathrm{feature} \mathrm{matrix} \mathrm{for} m^{th}$$\mathrm{class} \mathrm{and} m = 1,2, \dots ,O$$\mathrm{and} S$ is the number of the examples in a given class. S1: Calculate the centroid of the class m as: $F_c^m=\frac{1}{S}{\displaystyle \sum }_{s=1}^S{f}_s$ S2: Calculate the Euclidean distance between each example and centroid vectors as: $L_{mc}=\left|\left|f_m-F_c^m\right|\right|$