1 / 87

Image Processing

Image Processing. 主講人：虞台文. Content. Smoothing Image Morphology Some Applications of Image Morphology Flood Fill Resize Image Pyramids Threshold. Image Processing. Smoothing. Smoothing. Smoothing is also called blurring Why smoothing? reduce noise and camera artifact

jesse
Télécharger la présentation

Image Processing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Image Processing 主講人：虞台文

  2. Content • Smoothing • Image Morphology • Some Applications of Image Morphology • Flood Fill • Resize • Image Pyramids • Threshold

  3. Image Processing Smoothing

  4. Smoothing • Smoothing is also called blurring • Why smoothing? • reduce noise and camera artifact • reduce the resolution of an image in a principled way

  5. Smoothing smoothtype: CV_BLUR_NO_SCALE CV_BLUR CV_GAUSSIAN CV_MEDIAN CV_BILATERAL void cvSmooth( const CvArr* src, CvArr* dst, int smoothtype=CV_GAUSSIAN, int param1=3, int param2=0, double param3=0, double param4=0 ); Depending on smoothtype

  6. Smoothing

  7. Smoothing

  8. Original Example cvSmooth BLUR GAUSSIAN param1=7 param2=7 param1=7 param2=7 MEDIAN BILATERAL param1=7 param3=50.0 Param4=3.5 param1=7

  9. Exercise Download Test Program

  10. Image Processing Image Morphology

  11. Morphing Morphological Operations • Morphological operations come from the word “morphing” in Biology which means “changing a shape”.

  12. Morphological Operations • Originated fromset operations • Can be used to manipulate object shapes such as thinning, thickening, filling, etc.

  13. 0 0 1 0 0 0 0 1 0 0 1 1 1 1 1 0 0 1 0 0 0 0 1 0 0 A Binary Image Representation

  14. Basic Set Operations

  15. A (A)z Translation and Reflection Operations Translation Reflection

  16. Logical Operations

  17. Basic Morphological Operations • Dilation • Enlarge a region • Erosion • Shrink a region • Opening • Get rid ofsmall portions of region that jut out from the boundary into the background region • Closing • Close upinternal holes in a region and eliminate “bays” along the boundary

  18. Structure Element Morphological Operation Basic Morphological Operations • Defined based on a structure element 

  19. Structure Elements

  20. Dilation A = Object to be dilated B = Structuring element

  21. B A Dilation

  22. Dilation

  23. Erosion A = Object to be eroded B = Structuring element

  24. B A Erosion

  25. Erosion

  26. Example: Application of Dilation and Erosion Remove small objects such as noise

  27. Duality Between Dilation and Erosion Pf)

  28. Opening

  29. Opening eliminates narrow and small details and corners. Opening Combination of all parts of Athat can completely contain B

  30. Example: Opening

  31. Example: Opening

  32. Closing

  33. Closing fillsnarrow gaps and notches Closing

  34. Example: Closing

  35. Example: Closing

  36. Opening vs. Closing • Duality • Properties of Opening • Properties of Closing Idempotent property: can’t change any more

  37. Example: Application of Morphological Operations Finger print enhancement

  38. Example: Application of Morphological Operations Finger print enhancement

  39. Image Processing Some Applications of Image Morphology

  40. * X W  X W Hit-or-Miss Transformation  Xc

  41. * Hit-or-Miss Transformation Ac contains patternXc Acontains patternX

  42. * Hit-or-Miss Transformation

  43. * Hit-or-Miss Transformation

  44. Boundary Extraction A shrinks a little bit

  45. Boundary Extraction

  46. Boundary Extraction Original image Boundary

  47. Region Filling Make the filler inside A Enlarge the fillera little bit

  48. Region Filling Results of region filling Original image

  49. Extraction of Connected Components Make the extractorpart of A Enlarge the extractora little bit

  50. Extraction of Connected Components

More Related