Detail publikace

Rozpoznávání a třídění objektů podle tvaru

TOFEL, P.

Originální název

Rozpoznávání a třídění objektů podle tvaru

Anglický název

Object Sorting Based on Shape

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

čeština

Originální abstrakt

This paper presents modern science appears from the basis of Computer Vision and classifier of Synthetic Neural Network. A picture of watched object has to be taken in high quality with the best lighting and camera has to be situated vertically upon the object. Different camera positions does not assure exact results. Subsequently, image has to be transformed into binary image and purged from noise and other interference. Moments are used to describe separate objects in picture. Via the central moments and normed moments I count seven moments characteristic for each object to be identified. These moments are practically independent on rotation or changing scale of the object. They fluctuate only in a short spread. It is input to Neural Network, which is used as the classifier. The system of Back-propagation is used as the Neural Network with type of learning called learning with teacher. In my work, each letter of alphabet is used as the object to be identified. Further, I tried to identify object by using a tolerance. But as described before, the counting moments are not changeless. By the change of scale, moments fluctuate more than by rotation, thereafter if any value of identified object is out of the tolerance set, then we are not able to make the identification. Neural Network solve this problem. Enumeration of each moment and Neural Network is programmed in the Matlab 6.5 environment.

Anglický abstrakt

This paper presents modern science appears from the basis of Computer Vision and classifier of Synthetic Neural Network. A picture of watched object has to be taken in high quality with the best lighting and camera has to be situated vertically upon the object. Different camera positions does not assure exact results. Subsequently, image has to be transformed into binary image and purged from noise and other interference. Moments are used to describe separate objects in picture. Via the central moments and normed moments I count seven moments characteristic for each object to be identified. These moments are practically independent on rotation or changing scale of the object. They fluctuate only in a short spread. It is input to Neural Network, which is used as the classifier. The system of Back-propagation is used as the Neural Network with type of learning called learning with teacher. In my work, each letter of alphabet is used as the object to be identified. Further, I tried to identify object by using a tolerance. But as described before, the counting moments are not changeless. By the change of scale, moments fluctuate more than by rotation, thereafter if any value of identified object is out of the tolerance set, then we are not able to make the identification. Neural Network solve this problem. Enumeration of each moment and Neural Network is programmed in the Matlab 6.5 environment.

Klíčová slova

Neuronove sitě; rozpoznávání obrazu

Klíčová slova v angličtině

Neural Network; Back-propagation; Computer Vision

Autoři

TOFEL, P.

Rok RIV

2007

Vydáno

19. 1. 2007

Nakladatel

VUT Brno UFYZ

Místo

Brno

ISBN

978-80-7355-075-2

Kniha

NOVÉ TRENDY V MIKROELEKTRONICKÝCH SYSTÉMECH A NANOTECHNOLOGIÍCH

Číslo edice

První

Strany od

121

Strany do

125

Strany počet

5

URL

Knihovna UFYZ

BibTex

@inproceedings{BUT23275,
  author="Pavel {Tofel}",
  title="Rozpoznávání a třídění objektů podle tvaru",
  booktitle="NOVÉ TRENDY V MIKROELEKTRONICKÝCH SYSTÉMECH A NANOTECHNOLOGIÍCH",
  year="2007",
  number="První",
  pages="121--125",
  publisher="VUT Brno UFYZ",
  address="Brno",
  isbn="978-80-7355-075-2",
  url="Knihovna UFYZ"
}