COMP 9517 WK4
2021 T1
Image Features
• Image features are essentially vectors that are a compact representation of images
• They represent important information shown in an image
• Intuitive examples of image features: • Blobs
• Edges
• Corners • Ridges • Circles • Ellipses • Lines •…
Image Features
• We need to represent images as feature vectors for further processing in a more efficient and robust way
• Example of further processing include: • Object detection
• Image segmentation
• Image classification
• Content-based image retrieval • Image stitching
• Object tracking
Properties of Features
• Why not just use pixels values directly? • Repeatability (robustness)
• Should be detectable at the same locations in different images despite changes in illumination and viewpoint
• Saliency (descriptiveness)
• Similar salient points in different images should have similar features
• Compactness (efficiency) • Fewer features
• Smaller features
General Framework
Feature Types
• Colour features
• Colour histogram • Colour moments
• Texture features
• Haralick texture features
• Local binary patterns (LBP)
• Scale-invariant feature transform (SIFT) • Texture feature encoding
• Shape features
• Basic shape features
• Shape context
• Histogram of oriented gradients (HOG)
Colour Features
Colour Histogram
Colour Moments
Texture Features
• Texture is a powerful discriminating feature for identifying visual patterns with properties of homogeneity that can not result from the presence of only a single colour or intensity
Haralick Features
Haralick Features
Haralick Features
Haralick Features
Local Binary Patterns
Local Binary Patterns
Local Binary Patterns
Local Binary Patterns
Local Binary Patterns
Scale-Invariant Feature Transform
SIFT Extrema Detection
SIFT Keypoint Localization
SIFT Orientation Assignment
SIFT Keypoint Descriptor
Descriptor Matching
Transformation
Transformations
Fitting and Alignment
Fitting and Alignment
Fitting and Alignment
Fitting and Alignment
Fitting and Alignment
Fitting and Alignment
Fitting and Alignment
Alignment by Least Squares
Alignment by RANSAC
Feature Encoding
Feature Encoding
Feature Encoding
Feature Encoding
Feature Encoding
Feature Encoding
Feature Encoding
Application Example
Application Example
Shape Features
Boundary Descriptors
Shape Context
Shape Context
Shape Context
Shape Context
Shape Context
Shape Matching Example
Histogram of Oriented Gradients
Histogram of Oriented Gradients
Histogram of Oriented Gradients
Histogram of Oriented Gradients
Histogram of Oriented Gradients
HOG Application Example