Fusion of Face and speech for Multi-modal Person Identification System
M.Tech, ECE Department, SDMCET, Dharwad, India
ABSTRACT
A proposed new technique for person identification using fusion of both face and speech which can essentially improve the recognition rate as compared to the single biometric human identification. The proposed system uses Principal component analysis technique for face feature extraction. The PCA calculates the eigen vectors and eigen values which are used in fusion. The Singular spectrum analysis is used to extract speech features and the values of power spectrum are used in the fusion. The fusion of face and speech is done by simple sum rule fusion technique and normalization of feature values are done before the fusion. Person identification is depending on the fused results so that a Euclidean distance measures is used to find the variations in fused results.
