Text detection in natural and computer-generated images

Azmi Can Özgen; Mandana Fasounaki; Hazim Kemal Ekenel

doi:10.1109/SIU.2018.8404600

Text detection in natural and computer-generated images

Azmi Can Özgen
, Mandana Fasounaki
, Hazim Kemal Ekenel

Bilgisayar Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

10 Atıf (Scopus)

Özet

Text detection is one of the most challenging and commonly dealt applications in computer vision. Detecting text regions is the first step of the text recognition systems called Optical Character Recognition. This process requires the separation of text region from non-text region. In this paper, we utilize Maximally Stable Extremal Regions to acquire very first text region candidates. Then these possible regions are reduced in quantity by using geometric and stroke width properties. Candidate regions are joined to obtain text groups. Finally, Tesseract Optical Character Recognition engine is utilized as the last step to eliminate non-text groups. We evaluated the proposed system on KAIST and ICDAR datasets for both natural images and computer-generated images. For natural images 82.7% precision and 52.0% f-accuracy; for computer-generated images 64.0% precision and 65.2% f-accuracy is achieved.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	1-4
Sayfa sayısı	4
ISBN (Elektronik)	9781538615010
DOI'lar	https://doi.org/10.1109/SIU.2018.8404600
Yayın durumu	Yayınlandı - 5 Tem 2018
Etkinlik	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 - Izmir, Türkiye Süre: 2 May 2018 → 5 May 2018

Yayın serisi

Adı	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Ülke/Bölge	Türkiye
Şehir	Izmir
Periyot	2/05/18 → 5/05/18

Bibliyografik not

Publisher Copyright:
© 2018 IEEE.

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

SKH 3 Sağlık ve Kaliteli Yaşam

Belgeye Erişim

10.1109/SIU.2018.8404600

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Özgen, A. C., Fasounaki, M., & Ekenel, H. K. (2018). Text detection in natural and computer-generated images. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 (pp. 1-4). (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2018.8404600

@inproceedings{0247f77b3353479f81ba80d3ced4583d,

title = "Text detection in natural and computer-generated images",

abstract = "Text detection is one of the most challenging and commonly dealt applications in computer vision. Detecting text regions is the first step of the text recognition systems called Optical Character Recognition. This process requires the separation of text region from non-text region. In this paper, we utilize Maximally Stable Extremal Regions to acquire very first text region candidates. Then these possible regions are reduced in quantity by using geometric and stroke width properties. Candidate regions are joined to obtain text groups. Finally, Tesseract Optical Character Recognition engine is utilized as the last step to eliminate non-text groups. We evaluated the proposed system on KAIST and ICDAR datasets for both natural images and computer-generated images. For natural images 82.7\% precision and 52.0\% f-accuracy; for computer-generated images 64.0\% precision and 65.2\% f-accuracy is achieved.",

keywords = "Geometric and stroke width properties, Maximally stable extremal regions, Non-text region elimination, Text detection",

author = "{\"O}zgen, \{Azmi Can\} and Mandana Fasounaki and Ekenel, \{Hazim Kemal\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 ; Conference date: 02-05-2018 Through 05-05-2018",

year = "2018",

month = jul,

day = "5",

doi = "10.1109/SIU.2018.8404600",

language = "English",

series = "26th IEEE Signal Processing and Communications Applications Conference, SIU 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--4",

booktitle = "26th IEEE Signal Processing and Communications Applications Conference, SIU 2018",

address = "United States",

}

Özgen, AC, Fasounaki, M & Ekenel, HK 2018, Text detection in natural and computer-generated images. in 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Izmir, Türkiye, 2/05/18. https://doi.org/10.1109/SIU.2018.8404600

Text detection in natural and computer-generated images. / Özgen, Azmi Can; Fasounaki, Mandana; Ekenel, Hazim Kemal.
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-4 (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Text detection in natural and computer-generated images

AU - Özgen, Azmi Can

AU - Fasounaki, Mandana

AU - Ekenel, Hazim Kemal

PY - 2018/7/5

Y1 - 2018/7/5

N2 - Text detection is one of the most challenging and commonly dealt applications in computer vision. Detecting text regions is the first step of the text recognition systems called Optical Character Recognition. This process requires the separation of text region from non-text region. In this paper, we utilize Maximally Stable Extremal Regions to acquire very first text region candidates. Then these possible regions are reduced in quantity by using geometric and stroke width properties. Candidate regions are joined to obtain text groups. Finally, Tesseract Optical Character Recognition engine is utilized as the last step to eliminate non-text groups. We evaluated the proposed system on KAIST and ICDAR datasets for both natural images and computer-generated images. For natural images 82.7% precision and 52.0% f-accuracy; for computer-generated images 64.0% precision and 65.2% f-accuracy is achieved.

AB - Text detection is one of the most challenging and commonly dealt applications in computer vision. Detecting text regions is the first step of the text recognition systems called Optical Character Recognition. This process requires the separation of text region from non-text region. In this paper, we utilize Maximally Stable Extremal Regions to acquire very first text region candidates. Then these possible regions are reduced in quantity by using geometric and stroke width properties. Candidate regions are joined to obtain text groups. Finally, Tesseract Optical Character Recognition engine is utilized as the last step to eliminate non-text groups. We evaluated the proposed system on KAIST and ICDAR datasets for both natural images and computer-generated images. For natural images 82.7% precision and 52.0% f-accuracy; for computer-generated images 64.0% precision and 65.2% f-accuracy is achieved.

KW - Geometric and stroke width properties

KW - Maximally stable extremal regions

KW - Non-text region elimination

KW - Text detection

UR - https://www.scopus.com/pages/publications/85050822432

U2 - 10.1109/SIU.2018.8404600

DO - 10.1109/SIU.2018.8404600

M3 - Conference contribution

AN - SCOPUS:85050822432

T3 - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

SP - 1

EP - 4

BT - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

Y2 - 2 May 2018 through 5 May 2018

ER -

Text detection in natural and computer-generated images

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

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