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Gabor Filter Based Face Recognition Using Non-frontal Face Images

Authors:

Atrayee Majumder,

Srija Chowdhury,

Jaya SilAuthors Info & Claims

WCI '15: Proceedings of the Third International Symposium on Women in Computing and Informatics

Pages 419 - 425

https://doi.org/10.1145/2791405.2791505

Published: 10 August 2015 Publication History

Abstract

Face recognition has immense real world applications in the field of computer vision and a challenging task especially when the frontal face images are not available to train the classifiers. In this paper by regulating the scale and orientation parameters of Gabor Filters, we obtain high dimensional features from the face images with different poses. To classify the images, first we partition the images using k-means clustering algorithm where k varies from 6 to 8 for different databases representing pose variations of input images. Based on the clustering we assign class labels to the training data set for recognizing non-frontal face images with variant poses. To reduce the complexity of the system, different statistical properties of the features like variance, entropy, and correlation coefficient are analysed to select significant features only. Removal of irrelevant features, effectively reduces dimensionality of the feature space without sacrificing accuracy which is 94.47%. The proposed approach performs better compare to the existing methods, with and without feature selection algorithm.

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Cited By

Upadhyay VKotak D(2020)A Review on Different Facial Feature Extraction Methods for Face Emotions Recognition System2020 Fourth International Conference on Inventive Systems and Control (ICISC)10.1109/ICISC47916.2020.9171172(15-19)Online publication date: Jan-2020
https://doi.org/10.1109/ICISC47916.2020.9171172

Index Terms

Gabor Filter Based Face Recognition Using Non-frontal Face Images
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object recognition
      2. Computer vision tasks
        Scene understanding

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Published In

cover image ACM Other conferences

WCI '15: Proceedings of the Third International Symposium on Women in Computing and Informatics

August 2015

763 pages

ISBN:9781450333610

DOI:10.1145/2791405

Editor:
Indu Nair
SCMS, Kochi, India
,
General Chairs:
Sushmita Mitra
Indian Statistical Institute, Kolkata, India
,
Ljiljana Trajković
Simon Fraser University, Canada
,
Program Chairs:
Punam Bedi
University of Delhi, India
,
Suzanne McIntosh
New York University and Cloudera Inc., USA
,
M. S. Rajasree
IIITM-K, Trivandrum, India

Copyright © 2015 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 August 2015

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WCI '15

WCI '15: Third International Symposium on Women in Computing and Informatics

August 10 - 13, 2015

Kochi, India

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WCI '15 Paper Acceptance Rate 98 of 452 submissions, 22%;

Overall Acceptance Rate 98 of 452 submissions, 22%

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Cited By

Upadhyay VKotak D(2020)A Review on Different Facial Feature Extraction Methods for Face Emotions Recognition System2020 Fourth International Conference on Inventive Systems and Control (ICISC)10.1109/ICISC47916.2020.9171172(15-19)Online publication date: Jan-2020
https://doi.org/10.1109/ICISC47916.2020.9171172

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