Publication result detail

Gender Recognition Using PCA and DCT of Face Images

ŠMIRG, O.; FAÚNDEZ ZANUY, M.; GRASSI, M.; MEKYSKA, J.; MIKULKA, J.

Original Title

Gender Recognition Using PCA and DCT of Face Images

English Title

Gender Recognition Using PCA and DCT of Face Images

Type

Peer-reviewed article not indexed in WoS or Scopus

Original Abstract

In this paper we propose a gender recognition algorithm of face images. We have used PCA and DCT for dimensionality reduction. The algorithm is based on a genetic algorithm to improve the selection of training set of images for the PCA algorithm. Genetic algorithm helps to select the images, which best represent each gender, from the image database. We have evaluated a nearest neighbor classifier as well as a neural network. Experimental results show a correct identification rate of 85,9%.

English abstract

In this paper we propose a gender recognition algorithm of face images. We have used PCA and DCT for dimensionality reduction. The algorithm is based on a genetic algorithm to improve the selection of training set of images for the PCA algorithm. Genetic algorithm helps to select the images, which best represent each gender, from the image database. We have evaluated a nearest neighbor classifier as well as a neural network. Experimental results show a correct identification rate of 85,9%.

Keywords

PCA, DCT, gender recognition, face, Genetic algorithm

Key words in English

PCA, DCT, gender recognition, face, Genetic algorithm

Authors

ŠMIRG, O.; FAÚNDEZ ZANUY, M.; GRASSI, M.; MEKYSKA, J.; MIKULKA, J.

RIV year

2012

Released

10.06.2011

Publisher

Springer-Verlag

Location

Berlin Heidelberg

ISBN

0302-9743

Periodical

Lecture Notes in Computer Science

Volume

6692

Number

6

State

Federal Republic of Germany

Pages from

220

Pages to

227

Pages count

7

BibTex

@article{BUT36035,
  author="Ondřej {Šmirg} and Marcos {Faúndez Zanuy} and Marco {Grassi} and Jiří {Mekyska} and Jan {Mikulka}",
  title="Gender Recognition Using PCA and DCT of Face Images",
  journal="Lecture Notes in Computer Science",
  year="2011",
  volume="6692",
  number="6",
  pages="220--227",
  issn="0302-9743"
}