PCA based Multimodal Biometrics using Ear and Face Modalities

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Author(s)

Snehlata Barde 1,* A S Zadgaonkar 2 G R Sinha 3

1. Computer Faculty of Engineering and Technology, Shri Shankaracharya Group of Institutions Bhilai, C.G., India

2. Vice Chancellor, CV Raman University Bilaspur, C.G., India

3. Faculty of Engineering and Technology, Shri Shankaracharya Group of Institutions Bhilai, C.G., India

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2014.05.06

Received: 10 Aug. 2013 / Revised: 3 Dec. 2013 / Accepted: 20 Jan. 2014 / Published: 8 Apr. 2014

Index Terms

Biometrics, Principal Component Analysis (PCA), Eigen Faces, Eigen Ears, Euclidian Distance Hierarchical Matching, Calligraphic Retrieval, Skeleton Similarity

Abstract

Automatic person identification is an important task in computer vision and related applications. Multimodal biometrics involves more than two modalities. The proposed work is an implementation of person identification fusing face and ear biometric modalities. We have used PCA based neural network classifier for feature extraction from the images. These features are fused and used for identification. PCA method was found better if the modalities were combined. Identification was made using Eigen faces, Eigen ears and their features. These were tested over own created database.

Cite This Paper

Snehlata Barde, A S Zadgaonkar, G R Sinha, "PCA based Multimodal Biometrics using Ear and Face Modalities", International Journal of Information Technology and Computer Science(IJITCS), vol.6, no.5, pp.43-49, 2014. DOI:10.5815/ijitcs.2014.05.06

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