Gradient magnitude

The gradient-based segmentation, instead, allows to directly find the edges by their high-gradient magnitudes. 

You can change what is plotted, too. Figure D.13 shows that the temperature is to be plotted. To view the properties that can be plotted, select the predefined tab. They include temperature, heat flux,. v-cornpoiient and y-cornponent, heat flux (the magnitude), temperature gradient (magnitude), density, heat capacity, and heat source. This is where you get to explore your solution by plotting many features of it. It is also possible to plot one variable with the surface plot and another with the contour plot. 

Fig. 23 Sensitivity of the gradient magnitude edge detector to noise original image after edge detection (top) original image with added Gaussian noise (ff = 20) after edge detection (bottom).

The other directional gradient 0I(x,y)/0y can be discretised in a similar manner. From the discrete forms we are able to calculate the gradient magnitude of each image point and compare it with the threshold. Thus, we can locate all edge points. 

If we want to locate the positions of rapid variation of I(x,y), we should consider the local maxima of the gradient magnitude at various scales. The gradient magnitude at various scales is given by... 

Only those pixels whose gradient magnitude is larger than a predefined threshold are identified as edge pixels. 

If we compare the pressure gradient magnitude field (Figures 6a, 8 and 9) with the Principle Stress Difference (PSD) field for studied virtual die (Figures 6b) we can see that sensitivity of the Vp to the transition smoothness into the diverging channel is mnch higher than in the case of the PSD. Finally, the normal component of the pressure... 

Figure 6 Flow of the viscoelastic melt inside the virtual extrusion die having diverging exit region with smooth (upper wall) and sharp (bottom wall) transition 6a) Predicted pressure gradient magnitude field 6b) Predicted principle stress difference field.

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