# Wolfram Mathematica

## Find and Extract Salient Image Regions

Saliency detection is a technique commonly used to find the conspicuous regions in an image, such as objects that capture your attention.

Compute a saliency measure for every pixel of an image.

In[1]:=
```i = \!\(\* GraphicsBox[ TagBox[RasterBox[CompressedData[" 1:eJwku2dUI2eav73v+//yfts9uzM76xmHdujcTc4ZRJBAAmWUEAIJUEJCEUWQ kJCEckBZKKGAEDlnuumc7Lbdttseh3HbHmfPOM942s1b3v85hU4plqqe+7nu 61cqnu/lIvv/33/7t38T/H/ADbJnuJ7P75Gi/gO4g+EIGAOcPhqEI+wb6OOX 9f4f4EH6//Nv//YX4O+3dfU4UzZMGleQlcONBNxZoRCllPdw6JCohRLxEuAd uUgMgkQbINLoUr0MTYNjmZQe3qBUbxlUq5kysdbo6GUMu+JJh9mbXZp1h+zf /v2b4yfHvx7/8vcfH/3jx0dPnnz16+Pv7ty6rtOM68f1EomEJ5A43KHMbPT+ y3cPd9e/+9vr927Hr++HP3pw7a8PXt5aXrZZnAMMPr6bQeeKlXqLwmgnMHgt HSgIHIbG4aVKk92bHJRImxFtVc0NZJZgYtInGVOLFUoimYrCkrppfdguLF8p yCyvj2pNffQBBotqtdnC0VQwPG21W5GUtkrUxfNNfzpZ/sz5ihwMrVvnc49a HBz5qG0qklhajmfnfJFoPJEMhaZCU17lqIAzRMN11UFxF2tgJytb8/B0Bo4y ROWIGhAYucltmZrBM9gmn58tljIkotTq+ohhvKgqp6HtNKyzYFBG56r7Okjn cbQcIqMI1ZMLI51s6fxDK+FPYOxzVR3P5IOeym94/nzls+fKnztT9FxB+Xkw tBaEPl0KPVHWfroOfa6k+Y8vFfx7Gbikph12sayCRGMSaPQ2DKa6uamxra2p rQnUVl7Veq6iOYc6RMVRe4akqqnkQmRmMbu244ukUvOrK7uXHIGYwe4fFCsJ vX0jeh1XJsivOZtfcSG/uBjUXDdA72lqaUBhYH10SjDsTc8mY8mE0WqTKlXp 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In[2]:=
`map = ImageAdjust@ImageSaliencyFilter[i, Method -> "ImageSignature"]`
Out[2]=

Segment and highlight the most salient region of the image.

In[3]:=
`mask = DeleteSmallComponents@Dilation[Binarize[map, 2/3], 2];`
In[4]:=
`HighlightImage[i, mask, "Lighten"]`
Out[4]=

Trim the image to the salient region.

In[5]:=
```ImageTrim[i, #, 10] & /@ ComponentMeasurements[mask, "BoundingBox"][[All, 2]]```
Out[5]=

Perform saliency detection and trimming on multiple images.

In[6]:=
```list = {\!\(\* GraphicsBox[ TagBox[RasterBox[CompressedData[" 1:eJxMvGd3I9mWpteSvuijfoJmps2tqjRMenjvvQ94770HCAKEIUEDGtB7700y k+ldmSx7q6tv9/S0WtKSWZqlPyAt/QK9wezREm5cFBIEwpyzz7OfHXEC/86T 1Ab+67/6q7/K/rd40rqLnEzGXdb9d/iHIZENBxN+nySR8wf9mWHPf4M3Q//V X/3Vf8b/ydccrlAgFItEEqPR6PV6PT6vzWFXqbXBaNTkIJQmscEtlRoZMj2L LaYyhVSenEETUXs5lAEe5zGF2ken0TjMQfYQhdMn1/L5IrpMKcwX0gGfTyqU inliHpsrFAp5PJ5UKpXJZWarxWAyujxum9VsNOhMBqPL4XQ4XFaL00zYLWaH 3mJR6Y0KjZ7NFYmlKpFYLhaLZXKpWCYaoPYzuPRh1tDfPfwbKn3YarFaTVa/ L4DddjrtNjuh06scdrPbaTcb9SqlnDwivy8aj+kMehyiEg+FQiqX6Y0Gh8sp kojxPpfLVavVSqWaOkzBdsQS5fAw+8kTSl8/5dHjPiqVLuAJJSKp2+mSy8k9 Uak0Wo3eZMSWLWqdhsflstlsgUCgUqsUahUFrcGg9g/2Pez56tHjr1hsKl+A v/LsdrtEImOxODy+mEbnSKRKpUojk8m0WrVOr1EoZCaTCf9EyxgJE96S4w8q vVKhlUlVLCavr3+Yw0NLqFQ6o1pjUKn1XJ4Iq5IrNHiXQmXK5Eq8pjM4WPkw jU1j8mgsLoPL5wiETPSvWIGvszkCfAubxheFIqlao9PqDHKFiiAser0Rx6XR 6LB5s9lstVoUKiXaB51lt9tCQX8umw5HIx6PR6VS6XWaTDpZLpawJGLxTC5T GR3z+aOBYCwUicYScbPZrtejO1xWm0um1Kn0FolSrzFaPIGw1elK5sp2T4Cw 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