Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition
Harbin Institute of Technology · Chinese Academy of Sciences
Abstract
For years, researchers in face recognition area have been representing and recognizing faces based on subspace discriminant analysis or statistical learning. Nevertheless, these approaches are always suffering from the generalizability problem. This paper proposes a novel non-statistics based face representation approach, local Gabor binary pattern histogram sequence (LGBPHS), in which training procedure is unnecessary to construct the face model, so that the generalizability problem is naturally avoided. In this approach, a face image is modeled as a "histogram sequence" by concatenating the histograms of all the local regions of all the local Gabor magnitude binary pattern maps. For recognition, histogram…
Citation impact
- FWCI
- 16.72
- Percentile
- 100%
- References
- 31
Authors
5Topics & keywords
- Pattern recognition (psychology)
- Artificial intelligence
- Histogram
- Facial recognition system
- Computer science
- Local binary patterns
- Face (sociological concept)
- Histogram matching
- Reduced inequalities