Publication detail

Evolutionary Design of Local Binary Pattern Feature Shapes for Object Detection

KADLČEK, F. FUČÍK, O.

Original Title

Evolutionary Design of Local Binary Pattern Feature Shapes for Object Detection

English Title

Evolutionary Design of Local Binary Pattern Feature Shapes for Object Detection

Type

conference paper

Language

en

Original Abstract

This paper deals with the evolutionary design of application specific feature shapes of Local Binary Pattern (LBP) features for object detection in image processing applications. LBP features are very often utilized in image classification systems which are used for pattern recognition. By using genetic algorithm the application of specific weak classifiers' feature shapes, which are highly optimized to achieve a better accuracy of the AdaBoost strong classifier, are being evolved.

English abstract

This paper deals with the evolutionary design of application specific feature shapes of Local Binary Pattern (LBP) features for object detection in image processing applications. LBP features are very often utilized in image classification systems which are used for pattern recognition. By using genetic algorithm the application of specific weak classifiers' feature shapes, which are highly optimized to achieve a better accuracy of the AdaBoost strong classifier, are being evolved.

Keywords

Local Binary Pattern (LBP), AdaBoost, Evolutionary design, feature shapes

RIV year

2012

Released

25.06.2012

Publisher

IEEE Computer Society

Location

Nuremberg

ISBN

978-1-4673-1914-0

Book

2012 NASA/ESA Adaptive Hardware and Systems (AHS-2012) Conference

Edition

CFP1263A-USB

Edition number

NEUVEDEN

Pages from

1

Pages to

8

Pages count

8

URL

BibTex


@inproceedings{BUT91499,
  author="Filip {Kadlček} and Otto {Fučík}",
  title="Evolutionary Design of Local Binary Pattern Feature Shapes for Object Detection",
  annote="This paper deals with the evolutionary design of application specific feature
shapes of Local Binary Pattern (LBP) features for object detection in image
processing applications. LBP features are very often utilized in image
classification systems which are used for pattern recognition. By using genetic
algorithm the application of specific weak classifiers' feature shapes, which are
highly optimized to achieve a better accuracy of the AdaBoost strong classifier,
are being evolved.",
  address="IEEE Computer Society",
  booktitle="2012 NASA/ESA Adaptive Hardware and Systems (AHS-2012) Conference",
  chapter="91499",
  edition="CFP1263A-USB",
  howpublished="online",
  institution="IEEE Computer Society",
  year="2012",
  month="june",
  pages="1--8",
  publisher="IEEE Computer Society",
  type="conference paper"
}