Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol 11, Issue 08, August 2024

Call for Paper

Vol 11, Issue 08, August 2024

Indexing

An Assimilated Face Recognition System With effective Gender Recognition Rate

Author : K. Akhil Sreenivasulu 1 L. Guru Kumar 2 Dr. G. Harinatha Reddy 3

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Date of Publication :8th March 2017

Abstract: Gender Recognition in Face Recognition System has prevalent applications in the fields of demographic data collection, video surveillance, security, retail advertising and marketing and it also plays a vital role on object recognition in robot research area, which has shown an intensive attention in the past few years.However, face recognition is still a challenging task since face images are easily confused by changes of the facial factors, such as illumination, pose, the different expressions, or glasses. The goal of this paper is to improve the effectiveness of gender recognition when there are affected(blurred) images in the dataset. We applied novel descriptor based COSFIRE filters to achieve the Gender Recognition[1] in the Face Recognition System. A COSFIRE filter is trainable, in that its selectivity is determined in an automatic configuration process that analyses a given prototype pattern of interest on FERET training set. Extensive experiments were conducted on the GENDER-FERET dataset which contains 474 training and 472 test samples and demonstrated robustness and effectiveness of the proposed model. It also outperforms an approach that relies on handcrafted features and an ensemble of classifiers.

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