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ECE472/572 - Lecture 14

ECE472/572 - Lecture 14 . Morphological Image Processing 11/17/11. Image Acquisition. Image Enhancement. Image Segmentation. Image Restoration. Representation & Description. Image Compression. Recognition & Interpretation. Image Coding. Morphological Image Processing.

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ECE472/572 - Lecture 14

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  1. ECE472/572 - Lecture 14 Morphological Image Processing 11/17/11

  2. Image Acquisition Image Enhancement Image Segmentation Image Restoration Representation & Description Image Compression Recognition & Interpretation Image Coding Morphological Image Processing Fourier & Wavelet Analysis Roadmap Preprocessing – low level Knowledge Base

  3. Color image processing Interpreting color Pseudo-color IP Full-color IP Tonal vs. Color correction Enhancement and restoration (I vs. RGB channels) Color image edge detection Image compression Concept Data vs. information Entropy 3 types of data redundancy Fidelity measurement Lossless compression Variable length coding (Huffman coding) LZW Bitplane coding Binary image compression (RLC) Lossless predictive coding Lossy compression Lossy predictive coding JPEG Wavelet analysis WT vs. FT vs. STFT Time vs. Frequency resolution DWT Binary morphological image processing Morphological operators Dilation Erosion Opening Closing Morphological filter Hit-or-miss Gray-scale morphological image processing Applications Roadmap

  4. Questions • What is SE? • How to get the following effects • a sunken effect, • a relief effect, • the boundary • Remove noise in the background • Remove noise in the foreground • Link edges • Denoising in general • Shape recognition • Filling holes (conditional dilation)

  5. Morphology • Pre- and post-processing • Morphological filter • Extract image components that are useful in the representation and description • Boundary • Skeleton

  6. Morphological Operators - Dilation 4 3 2 1 0 -1 -2 -3 -4 -5 9 8 7 6 5 4 3 2 1 0 9 8 7 6 5 4 3 2 1 0 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 -5 -4 –3 –2 –1 0 1 2 3 4 A = {(2,8),(3,6),(4,4), (5,6),(6,4),(7,6),(8,8)} A+B = {(2,8),(3,6),(4,4), (5,6),(6,4),(7,6),(8,8), (2,9),(3,7),(4,5),(5,7), (6,5),(7,7),(8,9)} B = {(0,0),(0,1)} B: structuring element (s.e) Always includes (0,0)

  7. Morphological Operators - Erosion 9 8 7 6 5 4 3 2 1 0 9 8 7 6 5 4 3 2 1 0 2 1 0 -1 -2 –2 –1 0 1 2 B 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 A-B A

  8. Example

  9. Other Morphological Operators • Opening • Closing • Application???

  10. Example Opening Closing

  11. Morphological Filter (opening + closing)

  12. Application – Edge Linking

  13. Application

  14. The Hit-or-Miss Transformation B1 or D: shape of interest W: window W-D: window that surrounds D

  15. Some Basic Morphological Algorithms • Boundary extraction • Hole filling • Extraction of connected components • Skeletons

  16. Boundary Extraction

  17. Hole Filling X0 is a point within the region with holes. Conditional Dilation

  18. Extraction of Connected Components X0 is a point on the region. Conditional Dilation

  19. *Contex Hull Use hit-or-miss without background checking

  20. Gray-scale Morphology • Dilation • Finding max in the neighborhood • Erosion • Finding min in the neighborhood

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