(Für diese Definition ist die deutsche Übersetzung noch nicht abgeschlossen)
Feature extraction techniques that perform operations within image blocks or by using histograms.
Summation of image intensity values and projection along an axis, e.g. by binning the values into a histogram, to arrive at a more compact feature representation.
Notes – technical background
These notes provide more information about the technical subject matter that is classified in this place:
The processing classified in this group might involve:
- block-based arithmetic or logical operations (including non-linear operators such as “max”, “min”, etc.);
- histograms of various measurements computed on a block-basis, e.g. histogram of oriented gradients (HOG);
- quantification of local geometric arrangements of features by block-based analysis, e.g. local binary patterns (LBP).
The blocks need not necessarily be arranged in a form of a grid. They can overlap or can be arranged in different geometrical patterns.
Frequently used local feature descriptors which are classified in this group include:
- Histogram of oriented gradients (HOG);
- Edge oriented histogram (EOH);
- Local binary pattern (LBP) and its refinements:
- Shape context;
- Gradient location and orientation histogram (GLOH);
- Local energy based shape histogram (LESH);
- Oriented histogram of flows (OHF);
- Binary robust independent elementary features (BRIEF);
- Spin image.
Examples
The local oriented histograms of the gradients or HOG descriptor
The “shape context”, a representation which performs binning of the contours of the shape in a circular-like pattern
Global feature extraction by analysis of the whole pattern | G06V 10/42 |
Local feature extraction by analysis of parts of the pattern | G06V 10/44 |
Descriptors for shape, contour or point-related descriptors, e.g. SIFT | G06V 10/46 |
Image analysis in general | G06T 7/00 |