Algorithm 1 Serial implementation of Support Vector Machine

Input: $\mathit{\gamma }$ → Kernel parameter ${\mathit{D}\mathit{C}}_{\mathit{i}\mathit{j}}$ → Dual coefficients matrix ${\mathit{w}}_{\mathit{i}}$ → Support vectors matrix $\mathit{x}$ → Pixel to classify $\mathit{b}$ → Bias 1: $Step 1:Kernel calculation$ 2: $\mathbf{f}\mathbf{o}\mathbf{r} i=0 to {\mathit{n}}_{\mathit{s}\mathit{v}}-1$ 3:       $\mathit{K}\left({\mathit{w}}_{\mathit{i}},\mathit{x}\right)=\exp \left(-\gamma \ast {‖{\mathit{w}}_{\mathit{i}}-\mathit{x}‖}^2\right);$ 4: end 5: $Step 2:Distance of the sample from the hyperplane$ 6: $\mathbf{f}\mathbf{o}\mathbf{r} i=0 to {\mathit{n}}_{\mathit{c}\mathit{l}\mathit{a}\mathit{s}\mathit{s}}-1$ 7:        $\mathbf{f}\mathbf{o}\mathbf{r} j=i+1 to {\mathit{n}}_{\mathit{c}\mathit{l}\mathit{a}\mathit{s}\mathit{s}}-1$ 8:          ${\mathit{d}}_{\mathit{i}\mathit{j}}={\displaystyle \sum _{\mathit{i}€\mathit{S}\mathit{V}}\mathit{D}{\mathit{C}}_{\mathit{i}\mathit{j}}\ast \mathit{K}({\mathit{w}}_{\mathit{i}},\mathit{x})+\mathit{b};}$ 9:       end 10: end 11: Step 3: “One vs. one” strategy 12: $\mathbf{f}\mathbf{o}\mathbf{r} i=0 to {\mathit{n}}_{\mathit{c}\mathit{l}\mathit{a}\mathit{s}\mathit{s}}-1$ 13:       ${\mathit{s}\mathit{c}\mathit{o}\mathit{r}\mathit{e}}_{\mathit{i}}=0$ 14:       $\mathbf{f}\mathbf{o}\mathbf{r} j=i+1 to {\mathit{n}}_{\mathit{c}\mathit{l}\mathit{a}\mathit{s}\mathit{s}}-1$ 15:             $\mathbf{i}\mathbf{f}{\mathit{d}}_{\mathit{i}\mathit{j}}>0$ 16:                    ${\mathit{s}\mathit{c}\mathit{o}\mathit{r}\mathit{e}}_{\mathit{i}}++;$ 17:             $\mathbf{e}\mathbf{l}\mathbf{s}\mathbf{e}$ 18:                   ${\mathit{s}\mathit{c}\mathit{o}\mathit{r}\mathit{e}}_{\mathit{j}}++;$ 19:       end 20: end 21:  $\mathrm{F}\mathrm{i}\mathrm{n}\mathrm{d} \mathit{i}\mathit{m}\mathit{a}\mathit{x}, \mathrm{i}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{x} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{h}\mathrm{e} {\mathit{s}\mathit{c}\mathit{o}\mathit{r}\mathit{e}}_{\mathit{i}} \mathrm{m}\mathrm{a}\mathrm{x}\mathrm{i}\mathrm{m}\mathrm{u}\mathrm{m}$ Output: $\mathit{i}\mathit{m}\mathit{a}\mathit{x}$