... | ... | @@ -12,7 +12,7 @@ And the value of $`G^2`$ for a region of interest (ROI) is |
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```math
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G^2 = \frac{1}{N}\sum_{ij\in ROI} \nabla I^2_{ij}
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```
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where $`N`$ is the number of pixels inside the ROI. As an example, the top-left figure below shows an experimental image for a disc under diametric loading and the lower-left figure below shows the $`G^2`$ image calculated based on the experimental image. Both figures are colormap images: red means large value and blue means small value. For the $`G^2`$ image, the value of each pixel is the gradient square $`\nabla I^2`$ of the experimental image. The $`G^2`$ value for this disc is calculated by averaging the $`\nable I`$ values inside the disc, which is the ROI of the problem.
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where $`N`$ is the number of pixels inside the ROI. As an example, the top-left figure below shows an experimental image for a disc under diametric loading and the lower-left figure below shows the $`G^2`$ image calculated based on the experimental image. Both figures are colormap images: red means large value and blue means small value. For the $`G^2`$ image, the value of each pixel is the gradient square $`\nabla I^2`$ of the experimental image. The $`G^2`$ value for this disc is calculated by averaging the $`\nabla I`$ values inside the disc, which is the ROI of the problem.
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![demo1](uploads/922ae0b296375c84ed95e7045279231a/demo1.png)
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