Hyperspectral Face Recognition by Texture Feature Extraction Using Hybrid Wavelets Type I & Ii and Kekre Wavelet Transform

Distinct from other normal images, hyper spectral images consist of huge data, but its analysis requires deep understanding of exactly of what properties are to be measured and their relation to the actual measurements made by Hyper spectral sensor. With the enhancement and obtain ability of such Hyper spectral face data has increased the possibility of building such systems. The emphasis of this research is to recognize hyper spectral face images and compare the results obtained from the implementation of Multimodal system. The implementation of this System is based on three main texture feature extraction techniques. Hybrid Wavelet Type I (HWI), Hybrid Wavelet Type II (HWII) and Kekre Wavelet (KW) are used to generate these Multi Resolution Analysis based Feature Vectors. These Feature vector databases are then put through Intra Class testing And Inter Class Testing and their performance is evaluated and compared with existing systems. Proposed system has given up to 77% of EER for TAR-TRR (PI) for the multimodal implementation.