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Face Recognition using Fast Fourier Transform

Face Recognition using Fast Fourier Transform

Shivakumar Baragi, Nalini C. Iyer
Copyright: © 2016 |Pages: 21
ISBN13: 9781466687370|ISBN10: 1466687371|EISBN13: 9781466687387
DOI: 10.4018/978-1-4666-8737-0.ch017
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MLA

Baragi, Shivakumar, and Nalini C. Iyer. "Face Recognition using Fast Fourier Transform." Research Advances in the Integration of Big Data and Smart Computing, edited by Pradeep Kumar Mallick, IGI Global, 2016, pp. 302-322. https://doi.org/10.4018/978-1-4666-8737-0.ch017

APA

Baragi, S. & Iyer, N. C. (2016). Face Recognition using Fast Fourier Transform. In P. Mallick (Ed.), Research Advances in the Integration of Big Data and Smart Computing (pp. 302-322). IGI Global. https://doi.org/10.4018/978-1-4666-8737-0.ch017

Chicago

Baragi, Shivakumar, and Nalini C. Iyer. "Face Recognition using Fast Fourier Transform." In Research Advances in the Integration of Big Data and Smart Computing, edited by Pradeep Kumar Mallick, 302-322. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-8737-0.ch017

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Abstract

Biometrics refers to metrics related to human characteristics and Traits. Face Recognition is the process of identification of a person by their facial image. It has been an active area of research for several decades, but still remains a challenging problem because of the complexity of the human face. The objective is to authenticate a person, to have a FAR and FRR very low. This project introduces a new approach for face recognition system using FFT algorithm. The database that contains the images is named as train database and the test image which is stored in test database is compared with the created train database. For further processing RGB data is converted into grayscale, thus reduces the matrix dimension. FFT is applied to the entire database and mean value of the images is computed and the same is repeated on test database also. Based on the threshold value of the test image, face recognition is done. Performance evaluation of Biometrics is done for normal image, skin color image, ageing image and blur image using False Acceptance Rate(FAR), False Rejection Rate(FRR), Equal Error Rate(EER) and also calculated the accuracy of different images.

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