Detail publikace

Gender Recognition Using PCA and DCT of Face Images

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

Originální název

Gender Recognition Using PCA and DCT of Face Images

Typ

článek v časopise - ostatní, Jost

Jazyk

angličtina

Originální abstrakt

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%.

Klíčová slova

PCA, DCT, gender recognition, face, Genetic algorithm

Autoři

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

Rok RIV

2011

Vydáno

10. 6. 2011

Nakladatel

Springer-Verlag

Místo

Berlin Heidelberg

ISSN

0302-9743

Periodikum

Lecture Notes in Computer Science

Ročník

6692

Číslo

6

Stát

Spolková republika Německo

Strany od

220

Strany do

227

Strany počet

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"
}