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  • %22 Presented paper deals with the problem of determination of a selected object position and rotation in a given image. This task is quite common in various application of image processing like automatic control, biomedicine, quality engineering and others. Objects position and rotation evaluation is an important part of the recognition and classification processes. Method based on principal component analysis is studied in this contribution and its properties are exploited for object feature extraction in real images. Edge detection and thresholding methods were used for previous image segmentation. %22
  • %22 Presented paper deals with the problem of determination of a selected object position and rotation in a given image. This task is quite common in various application of image processing like automatic control, biomedicine, quality engineering and others. Objects position and rotation evaluation is an important part of the recognition and classification processes. Method based on principal component analysis is studied in this contribution and its properties are exploited for object feature extraction in real images. Edge detection and thresholding methods were used for previous image segmentation. %22 (en)
  • %22 Presented paper deals with the problem of determination of a selected object position and rotation in a given image. This task is quite common in various application of image processing like automatic control, biomedicine, quality engineering and others. Objects position and rotation evaluation is an important part of the recognition and classification processes. Method based on principal component analysis is studied in this contribution and its properties are exploited for object feature extraction in real images. Edge detection and thresholding methods were used for previous image segmentation. %22 (cs)
Title
  • Signal Feature Extraction Using Component Analysis Methods
  • Signal Feature Extraction Using Component Analysis Methods (en)
  • Signal Feature Extraction Using Component Analysis Methods (cs)
skos:prefLabel
  • Signal Feature Extraction Using Component Analysis Methods
  • Signal Feature Extraction Using Component Analysis Methods (en)
  • Signal Feature Extraction Using Component Analysis Methods (cs)
skos:notation
  • RIV/60461373:22340/06:00016754!RIV07-MSM-22340___
http://linked.open.../vavai/riv/strany
  • R116/2-R116/5
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM6046137306)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 499219
http://linked.open...ai/riv/idVysledku
  • RIV/60461373:22340/06:00016754
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Image Processing; Principal Component Analysis; Object Detection (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [268CD8CDC144]
http://linked.open...v/mistoKonaniAkce
  • Kouty nad Desnou
http://linked.open...i/riv/mistoVydani
  • Pardubice
http://linked.open...i/riv/nazevZdroje
  • Proceedings of 7th International Conference Process Control ŘÍP 2006
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Mudrová, Martina
  • Procházka, Aleš
  • Kolínová, Magdaléna
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Univerzita Pardubice
https://schema.org/isbn
  • 80-7194-860-8
http://localhost/t...ganizacniJednotka
  • 22340
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