Automated text detection and character recognition in natural scenes based on local image features and contour processing techniques

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10239792" target="_blank" >RIV/61989100:27240/18:10239792 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-319-73888-8_8" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-73888-8_8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-73888-8_8" target="_blank" >10.1007/978-3-319-73888-8_8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automated text detection and character recognition in natural scenes based on local image features and contour processing techniques

Popis výsledku v původním jazyce

A novel effective scheme for automated text detection and character recognition in natural scene images is presented in the paper. The proposed text detection approach belongs to the category of connected component-based methods utilizing Maximally Stable Extremal Regions (MSER) feature detector. Various literature based geometrical and contour oriented filters, used to distinguish between text and non-text MSER regions as well as to group remaining text regions into words and phrases, are applied first. Novel filters, designed to reject remaining non-text regions and words (phrases) that are not in line with assumed properties, are utilized next. Final words and phrases are recognized using an OCR system. Finally, an application of the presented approach within the IMCOP content discovery and delivery platform is briefly described. (C) Springer International Publishing AG 2018.

Název v anglickém jazyce

Automated text detection and character recognition in natural scenes based on local image features and contour processing techniques

Popis výsledku anglicky

A novel effective scheme for automated text detection and character recognition in natural scene images is presented in the paper. The proposed text detection approach belongs to the category of connected component-based methods utilizing Maximally Stable Extremal Regions (MSER) feature detector. Various literature based geometrical and contour oriented filters, used to distinguish between text and non-text MSER regions as well as to group remaining text regions into words and phrases, are applied first. Novel filters, designed to reject remaining non-text regions and words (phrases) that are not in line with assumed properties, are utilized next. Final words and phrases are recognized using an OCR system. Finally, an application of the presented approach within the IMCOP content discovery and delivery platform is briefly described. (C) Springer International Publishing AG 2018.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

Advances in Intelligent Systems and Computing. Volume 722

ISBN

978-3-319-73887-1

ISSN

2194-5357

e-ISSN

2194-5365

Počet stran výsledku

7

Strana od-do

42-48

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Dubaj

Datum konání akce

7. 1. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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