Course Syllabus Color Camera models, camera calibration Advanced image pre-processing

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Course Syllabus 1. Color 2. Camera models, camera calibration 3. Advanced image pre-processing Line detection Corner detection Maximally stable extremal regions 4. Mathematical Morphology binary gray-scale skeletonization granulometry morphological segmentation Scale in image processing 5. Wavelet theory in image processing 6. Image Compression 7. Texture 8. Image Registration rigid non-rigid RANSAC

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Course Syllabus Color Camera models, camera calibration Advanced image pre-processing Line detection Corner detection Maximally stable extremal regions Mathematical Morphology binary gray-scale skeletonization granulometry morphological segmentation Scale in image processing - PowerPoint PPT Presentation

Transcript of Course Syllabus Color Camera models, camera calibration Advanced image pre-processing

Page 1: Course Syllabus Color  Camera models, camera calibration Advanced image pre-processing

Course Syllabus

1. Color 2. Camera models, camera calibration3. Advanced image pre-processing

• Line detection• Corner detection• Maximally stable extremal regions

4. Mathematical Morphology • binary• gray-scale• skeletonization• granulometry• morphological segmentation• Scale in image processing

5. Wavelet theory in image processing6. Image Compression7. Texture8. Image Registration

• rigid• non-rigid• RANSAC

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1. Homotopy• Homotopic tree in 2D• Challenges in 3D

2. Sketonization and maximal ball• Maximal balls• Skeleton• Basis relation between maximal ball and skeleton• Mathematical formulation• Challenges

3. Morphological solution to homotopic skeletonization • Role of his and miss• Thinning, Thickening, and Duality• Iterative thinning: structuring element

4. Distance transform and thinning• Axial line detection using DT• Simple point• Thinning Algorithm

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Quiz

Object = black

original ? ?

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13.5 Skeletons and object marking

13.5.1 Homotopic transformations

• transformation is homotopic if it does not change the continuity relation between regions and holes in the image.

• this relation is expressed by homotopic treeo its root ... image backgroundo first-level branches ... objects (regions)o second-level branches ... holeso etc.

• transformation is homotopic if it does not change homotopic tree

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Homotopic Tree

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Homotopic Tree

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Homotopic Tree

r1 r2

h1

h2

br1

r2

h2

h1

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Quitz: Homotopic Transformation• What is the relation between an element in the ith and i+1th levels?

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More challenges in 3D • Lot more challenges in 3D• Homotopic tree is not feasible

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Sequential thinning by structuring element L

• thinning by L serves as homotopic substitute of the skeleton;• final thinned image consists only of lines of width one and isolated points

• structuring element L from the Golay alphabet is given by

• (The other six elements are given by rotation).

Original after 5 iteration final result

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Sequential thinning by structuring element E

• structuring element E from the Golay alphabet is given by

• Less jagged skeletons

Original skeleton

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Axial line detection using Distance transform

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Axial line detection using Distance transform

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Axial line detection using Distance transform