Automated region of interest retrieval of metallographic images for quality classification in industry

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86084961" target="_blank" >RIV/61989100:27240/12:86084961 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/12:86084961

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Automated region of interest retrieval of metallographic images for quality classification in industry

Popis výsledku v původním jazyce

The aim of the research is development and testing of new methods to classify the quality of metallographic samples of steels with high added value (for example grades X70 according API). In this paper, we address the development of methods to classify the quality of slab samples images with the main emphasis on the quality of the image center called as segregation area. For this reason, we introduce an alternative method for automated retrieval of region of interest. In the first step, the metallographic image is segmented using both spectral method and thresholding. Then, the extracted macrostructure of the metallographic image is automatically analyzed by statistical methods. Finally, automatically extracted region of interests are compared with results of human experts. Practical experience with retrieval of non-homogeneous noised digital images in industrial environment is discussed as well.

Název v anglickém jazyce

Automated region of interest retrieval of metallographic images for quality classification in industry

Popis výsledku anglicky

The aim of the research is development and testing of new methods to classify the quality of metallographic samples of steels with high added value (for example grades X70 according API). In this paper, we address the development of methods to classify the quality of slab samples images with the main emphasis on the quality of the image center called as segregation area. For this reason, we introduce an alternative method for automated retrieval of region of interest. In the first step, the metallographic image is segmented using both spectral method and thresholding. Then, the extracted macrostructure of the metallographic image is automatically analyzed by statistical methods. Finally, automatically extracted region of interests are compared with results of human experts. Practical experience with retrieval of non-homogeneous noised digital images in industrial environment is discussed as well.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

<a href="/cs/project/FR-TI1%2F432" target="_blank" >FR-TI1/432: *Nové moderní výpočetní metody pro řízení kvality v oblasti výroby náročných jakostí ocelí</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

Advances in Electrical and Electronic Engineering

ISSN

1336-1376

e-ISSN

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Svazek periodika

10

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

7

Strana od-do

51-56

Kód UT WoS článku

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EID výsledku v databázi Scopus

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