Face Recognition via the Overlapping Energy Histogram
MetadataShow full item record
In this paper we investigate the face recognition problem via the overlapping energy histogram of the DCT coefficients. Particularly, we investigate some important issues relating to the recognition performance, such as the issue of selecting threshold and the number of bins. These selection methods utilise information obtained from the training dataset. Experimentation is conducted on the Yale face database and results indicate that the proposed parameter selection methods perform well in selecting the threshold and number of bins. Furthermore, we show that the proposed overlapping energy histogram approach outperforms the Eigenfaces, 2DPCA and energy histogram significantly.
Showing items related by title, author, creator and subject.
Dagasan, Y.; Renard, P.; Straubhaar, J.; Erten, Oktay; Topal, Erkan (2018)The application of multiple-point statistics (MPS) in the mining industry is not yet widespread and there are very few applications so far. In this paper, we focus on the problem of algorithmic input parameter selection, ...
de V. Groenewald, J.; Coetzer, L.; Aldrich, Chris (2006)With the increasing availability of large amounts of real-time process data and a better fundamental understanding of the operation of mineral processing units, statistical monitoring of mineral processing plants is ...
Use of energy-filtered photoelectron emission microscopy and Kelvin probe force microscopy to visualise work function changes on diamond thin films terminated with oxygen and lithium mono-layers for thermionic energy conversionAndrade, H.; Othman, M.; O'Donnell, Kane; Lay, J.; May, P.; Fox, N.; Morin, J.; Renault, O. (2014)Kelvin probe force microscopy (KPFM) and energy-filtered photoelectron emission microscopy (EF-PEEM) with vacuum UV (VUV) excitation have been used to study the work function of p-type diamond films treated to exhibit a ...