The Comparative Recognition of Monochrome and Color Images Using Networks of N-Tuple and Min/Max Nodes Utilizing 'Grouped Nodes'

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F13%3A43919014" target="_blank" >RIV/49777513:23220/13:43919014 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

The Comparative Recognition of Monochrome and Color Images Using Networks of N-Tuple and Min/Max Nodes Utilizing 'Grouped Nodes'

Popis výsledku v původním jazyce

This paper documents the results obtainable when either networks of n-tuple (NT) logic nodes or Min/Max (MM) nodes are used to recognize monochrome and color images. Networks of n-tuple nodes are based upon the n-tuple methodology originated by Bledsoe and Browning. Networks of Min/Max nodes employ similar techniques but are capable of directly processing grey-scale values. Both networks are illustrated with appropriate diagrams. The comparative results indicate that color recognition generally providesimproved confidence levels. Also, overall, for 'equivalent' networks there are insignificant differences amongst the responses. By means of implementing grouping of the nodes, higher confidence levels can be obtained. Of importance, if a suitable threshold is applied to the summed values of grouped nodes, the nets can be configured to provide confidence levels approaching 100%. The documented methodologies are relatively simple to implement in either hardware or software, easy to use an

Název v anglickém jazyce

The Comparative Recognition of Monochrome and Color Images Using Networks of N-Tuple and Min/Max Nodes Utilizing 'Grouped Nodes'

Popis výsledku anglicky

This paper documents the results obtainable when either networks of n-tuple (NT) logic nodes or Min/Max (MM) nodes are used to recognize monochrome and color images. Networks of n-tuple nodes are based upon the n-tuple methodology originated by Bledsoe and Browning. Networks of Min/Max nodes employ similar techniques but are capable of directly processing grey-scale values. Both networks are illustrated with appropriate diagrams. The comparative results indicate that color recognition generally providesimproved confidence levels. Also, overall, for 'equivalent' networks there are insignificant differences amongst the responses. By means of implementing grouping of the nodes, higher confidence levels can be obtained. Of importance, if a suitable threshold is applied to the summed values of grouped nodes, the nets can be configured to provide confidence levels approaching 100%. The documented methodologies are relatively simple to implement in either hardware or software, easy to use an

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2013 International Conference on Applied Electronics

ISBN

978-80-261-0166-6

ISSN

1803-7232

e-ISSN

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Počet stran výsledku

6

Strana od-do

321-326

Název nakladatele

University of West Bohemia

Místo vydání

Pilsen

Místo konání akce

Pilsen

Datum konání akce

10. 9. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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