Publication detail

Comparison Methods for Object Recognition

ŠKORPIL, V. ŠŤASTNÝ, J.

Original Title

Comparison Methods for Object Recognition

Type

conference paper

Language

English

Original Abstract

This paper describes our new unpublished results and outputs of selected methods for object recognition. It is continued to our former research. We are focused to the identification with the aid of moments, with the aid of syntactical analysis and with the aid of neural network algorithms. Momentum method is very sensitive to entry image quality. Syntactic analysis is suitable for rotated objects, high-speed classification and for small changes in the segment edge. Neural network algorithms can be used for high-speed classification with randomly rotated objects and for some differences between learned etalons and classified objects.

Keywords

Neural network, Invariant moments, Primitives, Syntactical analysis, Back-propagation algorithm.

Authors

ŠKORPIL, V.; ŠŤASTNÝ, J.

RIV year

2009

Released

21. 7. 2009

Publisher

WSEAS

Location

Rhodos, Greece

ISBN

978-960-474-097-0

Book

Proceedings of the 13th WSEAS International Conference on Systems

Edition

WSEAS

Edition number

1

Pages from

607

Pages to

610

Pages count

4

BibTex

@inproceedings{BUT29438,
  author="Vladislav {Škorpil} and Jiří {Šťastný}",
  title="Comparison Methods for Object Recognition",
  booktitle="Proceedings of the 13th WSEAS International Conference on Systems",
  year="2009",
  series="WSEAS",
  number="1",
  pages="607--610",
  publisher="WSEAS",
  address="Rhodos, Greece",
  isbn="978-960-474-097-0"
}