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Section Navigation
Data
Operations on NumPy arrays
Using simple NumPy operations for manipulating images
Generate footprints (structuring elements)
Block views on images/arrays
Decompose flat footprints (structuring elements)
Manipulating exposure and color channels
RGB to grayscale
RGB to HSV
Histogram matching
Adapting gray-scale filters to RGB images
Filtering regional maxima
Separate colors in immunohistochemical staining
Gamma and log contrast adjustment
Histogram Equalization
Tinting gray-scale images
Edges and lines
Contour finding
Convex Hull
Canny edge detector
Marching Cubes
Active Contour Model
Ridge operators
Shapes
Random Shapes
Approximate and subdivide polygons
Straight line Hough transform
Circular and Elliptical Hough Transforms
Skeletonize
Edge operators
Geometrical transformations and registration
Swirl
Interpolation: Edge Modes
Rescale, resize, and downscale
Build image pyramids
Piecewise Affine Transformation
Structural similarity index
Using geometric transformations
Types of homographies
Use thin-plate splines for image warping
Fundamental matrix estimation
Robust line model estimation using RANSAC
Radon transform
Robust matching using RANSAC
Image registration
Image Registration
Masked Normalized Cross-Correlation
Assemble images with simple image stitching
Using Polar and Log-Polar Transformations for Registration
Filtering and restoration
Removing small objects in grayscale images with a top hat filter
Hysteresis thresholding
Image Deconvolution
Using window functions with images
Mean filters
Unsharp masking
Entropy
Image Deconvolution
Calibrating Denoisers Using J-Invariance
Fill in defects with inpainting
Band-pass filtering by Difference of Gaussians
Denoising a picture
Shift-invariant wavelet denoising
Phase Unwrapping
Non-local means denoising for preserving textures
Attribute operators
Wavelet denoising
Butterworth Filters
Full tutorial on calibrating Denoisers Using J-Invariance
Detection of features and objects
Dense DAISY feature description
Histogram of Oriented Gradients
Haar-like feature descriptor
Template Matching
Corner detection
Multi-Block Local Binary Pattern for texture classification
Filling holes and finding peaks
CENSURE feature detector
Removing objects
Blob Detection
ORB feature detector and binary descriptor
Gabors / Primary Visual Cortex “Simple Cells” from an Image
Fisher vector feature encoding
BRIEF binary descriptor
SIFT feature detector and descriptor extractor
GLCM Texture Features
Shape Index
Sliding window histogram
Gabor filter banks for texture classification
Local Binary Pattern for texture classification
Segmentation of objects
Region Boundary based Region adjacency graphs (RAGs)
Region adjacency graph (RAG) Thresholding
Normalized Cut
Find Regular Segments Using Compact Watershed
Thresholding
Drawing Region Adjacency Graphs (RAGs)
Chan-Vese Segmentation
Finding local maxima
Multi-Otsu Thresholding
Random walker segmentation
Apply maskSLIC vs SLIC
Niblack and Sauvola Thresholding
Expand segmentation labels without overlap
Watershed segmentation
Label image regions
Comparison of segmentation and superpixel algorithms
Find the intersection of two segmentations
Region Adjacency Graphs (RAGs)
Region adjacency graph (RAG) Merging
Measure perimeters with different estimators
Extrema
Explore and visualize region properties with pandas
Hausdorff Distance
Hierarchical Merging of Region Boundary RAGs
Morphological Snakes
Evaluating segmentation metrics
Flood Fill
Euler number
Longer examples and demonstrations
Render text onto an image
Face detection using a cascade classifier
Use pixel graphs to find an object’s geodesic center
Visual image comparison
Morphological Filtering
Comparing edge-based and region-based segmentation
Thresholding
Face classification using Haar-like feature descriptor
Examples for developers
Li thresholding
Max-tree
Examples
Data
Data
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