Facial Gender Analysis using Gabor-DWT Feature Extraction Method
Shubh Lakshmi Agrwal1, Neelam Kumari2, Vibhor Kant3, Shyam S. Agrawal4, Sandeep K. Gupta5
1Neelam Kumari, Department of Computer Science & Engineering, Govt. Women Engg. college, Ajmer, India.
2Shhubh Lakshmi Agrwal, Department of Computer Science & Engineering, LNM-IIT, Jaipur, India.
3Vibhor Kant, Department of Computer Science & Engineering, LNM-IIT, Jaipur, India.
4Shayam Sunder Agrawal, Department of Computer Science & Engineering, Govt. Women Engg. college, Ajmer, India.
5Sandeep K. Gupta, (Jekson Vision), Govt Engg College Jhalawar, India.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 4904-4907 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B4968129219/2019©BEIESP | DOI: 10.35940/ijeat.B4968.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Facial Gender Analysis has application of specific gender entry detection, human machine interface for digital marketing, real time targeted advertisement and gender demographic analysis. The facial gender can be predicted by classification 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 enhancement, 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.
Keywords: Gabor filter, DWT, Gender prediction.