Affine Normalized Krawtchouk Moments Based Face Recognition
| Autor: | B. H. Shekar, D. S. Rajesh |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Normalization (statistics)
Polynomial Krawtchouk moments matrix Face recognition Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Sparse approximation Facial recognition system ComputingMethodologies_PATTERNRECOGNITION Face (geometry) Canny edge detector General Earth and Planetary Sciences Krawtchouk polynomials Computer vision Artificial intelligence Affine transformation Focus (optics) business Sparse representation General Environmental Science |
| Zdroj: | Procedia Computer Science. 58:66-75 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2015.08.014 |
| Popis: | In this paper, we have developed a new local descriptor based on Krawtchouk polynomial moments. The interest points are initially detected using the Canny edge detector and made the region around each interest point scale and affine normalized. The region is then represented using Krawtchouk polynomial and hence formed the descriptor. Experiments have been conducted keeping the face recognition problem in focus. By using the sparse representation concept, classification of face images is done. Experimental results on the ORL dataset and a subset of pose and illumination variant FERET dataset have shown the classification capability of our descriptor for face recognition applications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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