Open AccessPerformance Evolution of Face and Speech Recognition system using DTCWT and MFCC Features
Author(s) -
Shanthakumar H.C et.al
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i3.1603
Subject(s) - computer science , mel frequency cepstrum , artificial intelligence , biometrics , speech recognition , facial recognition system , complex wavelet transform , pattern recognition (psychology) , face (sociological concept) , password , identification (biology) , feature extraction , wavelet transform , wavelet , discrete wavelet transform , computer network , social science , botany , sociology , biology
Every activity in day-to-day life is required the need of mechanized automation for ensuring the security. The biometrics security system provides the automatic recognition of human by overcoming the traditional recognition methods like Password, Personal Identification Number and ID cards etc. The face recognition is a wide research with many applications. In the proposed work face recognition is carried out using DTCWT (Dual Tree Complex Wavelet Transform) integrated with predominant QFT (Quick Fourier Transform) and speech recognition is carried out using MFCC (Mel Frequency Cepstral Coefficients) algorithm. The distance formula is used for matching the test features and database features of the face and speech images. Performance variables such as EER, FRR, FAR and TSR are evaluated for person recognition