Open AccessFacial Gender Analysis using Gabor-DWT Feature Extraction Method
Author(s) -
Neelam Kumari,
Shhubh Lakshmi Agrwal,
Vibhor Kant,
Shayam Sunder Agrawal,
Sandeep Gupta
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.b4968.129219
Subject(s) - artificial intelligence , computer science , gabor filter , pattern recognition (psychology) , face (sociological concept) , computer vision , feature extraction , redundancy (engineering) , dimensionality reduction , facial recognition system , gabor wavelet , face hallucination , biometrics , face detection , wavelet , social science , discrete wavelet transform , wavelet transform , sociology , operating system
Facial Gender Analysis has application of specific gender entry detection, human machine interface for digital marketing, real time targeted advertisement and gender demo-graphic analysis. The facial gender can be predicted by classifi-cation of the texture and unique edges pattern. Gabor filter can extract the edge- texture patterns on the face but has problem of high dimensionality with redundancy. For accuracy enhance-ment, the dimension and redundancy is needed to reduce by proposed technique as maxDWT feature optimization method. The proposed model is evaluated on real life challenging dataset of face as illumination variation, POSE, face profile, age variation and obstruction on face as hat, birthmark, moles, speckles, beard, etc. Results shows that proposed technique far better than existing state of art methods of gender prediction.