Analysis of Side View Face Recognition Using Gabor Filter and PCA Techniques

Authors

  • Abhilasha Joshi Dr. B. R. Ambedkar N.I.T. Jalandhar
  • Neetu Sood
  • Indu Saini

DOI:

https://doi.org/10.37591/joipprp.v4i2.1026

Abstract

Abstract

Recognition of human side face is being a dynamic research area in recent era. A different system for face recognition including side view confront has been proposed in this paper. Face recognition utilizing blocked face or using a small portion of the face is still an issue in human recognition which has incredible potential in criminological and security applications. The paper gives a concise thought regarding PCA and 2DGF systems and proposes a calculation which can be utilized for side-face recognition. The desired calculation separates facial features like eigen faces, edges and contour for extraction from information image. Recognition rate of this work is found to be 82% with 2DGF technique as shown in results. All face feature vectors are extracted and compared with same component of dataset images.

Keywords: Face recognition, PCA (Principal Component Analysis), 2DGF (Two Dimensional Gabor Filter), edges detection, contour detection, feature vector

Cite this Article

Abhilasha Joshi, Neetu Sood, Indu Saini. Analysis of Side View Face Recognition Using Gabor Filter and PCA Techniques. Journal of Image Processing & Pattern Recognition Progress. 2017; 4(2): 21–27p.


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Published

2017-08-18

Issue

Vol. 4 No. 2 (2017)

Section

Research Articles

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