WLD: A Robust Local Image Descriptor
University of Oulu · Institute of Computing Technology · +3 more institutions
Abstract
Inspired by Weber's Law, this paper proposes a simple, yet very powerful and robust local descriptor, called the Weber Local Descriptor (WLD). It is based on the fact that human perception of a pattern depends not only on the change of a stimulus (such as sound, lighting) but also on the original intensity of the stimulus. Specifically, WLD consists of two components: differential excitation and orientation. The differential excitation component is a function of the ratio between two terms: One is the relative intensity differences of a current pixel against its neighbors, the other is the intensity of the current pixel. The orientation component is the gradient orientation of the current pixel. For a given…
Citation impact
- FWCI
- 29.54
- Percentile
- 100%
- References
- 60
Authors
7Topics & keywords
- Artificial intelligence
- Pixel
- Pattern recognition (psychology)
- Histogram
- Computer science
- Computer vision
- Facial recognition system
- Orientation (vector space)
- Peace, Justice and strong institutions