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  1. Blending recap • Visible seams – edges that should not exist, should be avoided. • People are fairly insensitive to uniform intensity shifts or gradual intensity shifts.

  2. Morphological Operation • What if your images are binary masks? • Binary image processing is a well-studied field, based on set theory, called Mathematical Morphology Slides from Alexei Efros

  3. Preliminaries

  4. Preliminaries

  5. Preliminaries

  6. Basic Concepts in Set Theory • A is a set in , a=(a1,a2) an element of A, aA • If not, then aA • : null (empty) set • Typical set specification: C={w|w=-d, for d  D} • A subset of B: AB • Union of A and B: C=AB • Intersection of A and B: D=AB • Disjoint sets: AB=  • Complement of A: • Difference of A and B: A-B={w|w  A, w  B}=

  7. Preliminaries

  8. Dilation and Erosion • Two basic operations: • A is the image, B is the “structural element”, a mask akin to a kernel in convolution • Dilation : • (all shifts of B that have a non-empty overlap with A) • Erosion : • (all shifts of B that are fully contained within A)

  9. Dilation

  10. Dilation

  11. Erosion

  12. Erosion Original image Eroded image

  13. Erosion Eroded once Eroded twice

  14. Opening and Closing • Opening : smoothes the contour of an object, breaks narrow isthmuses, and eliminates thin protrusions • Closing : smooth sections of contours but, as opposed to opning, it generally fuses narrow breaks and long thin gulfs, eliminates small holes, and fills gaps in the contour • Prove to yourself that they are not the same thing. Play around with bwmorph in Matlab.

  15. Opening and Closing OPENING: The original image eroded twice and dilated twice (opened). Most noise is removed CLOSING: The original image dilated and then eroded. Most holes are filled.

  16. Opening and Closing

  17. Boundary Extraction

  18. Boundary Extraction