Parallel layer scanning based fast dot/dash line detection algorithm for large scale binary document images

Chinthaka Premachandra; H. Waruna H. Premachandra; Chandana D. Parape; Hiroharu Kawanaka

doi:10.1007/978-3-319-11758-4_43

Parallel layer scanning based fast dot/dash line detection algorithm for large scale binary document images

Chinthaka Premachandra, H. Waruna H. Premachandra, Chandana D. Parape, Hiroharu Kawanaka

Department of Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A fast dot/dash line detection method suitable for large scale binary document images is proposed. The method works by reducing the number of scanned pixels used for the detection process. In the new method, pixels in vertical image layers with only a constant spacing are scanned. By using this technique, the computational time can be reduced because some of the uninteresting objects in the image can easily be omitted in the scanning stage. The new method is faster than the conventional method not only due to its scanning method but it also due to the simple process used for detecting dot/dash lines. A dot/dash line is detected by selecting a small defined image domain from the large scale image. We evaluated the new method against conventional methods on appropriate document images and found an improved processing time without any significant loss of line detection ability.

Original language	English
Title of host publication	Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings
Editors	Mohamed Kamel, Aurélio Campilho
Publisher	Springer Verlag
Pages	395-402
Number of pages	8
ISBN (Electronic)	9783319117577
DOIs	https://doi.org/10.1007/978-3-319-11758-4_43
Publication status	Published - 2014 Jan 1
Event	11th International Conference on Image Analysis and Recognition, ICIAR 2014 - Vilamoura, Portugal Duration: 2014 Oct 22 → 2014 Oct 24

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8814
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	11th International Conference on Image Analysis and Recognition, ICIAR 2014
Country	Portugal
City	Vilamoura
Period	14/10/22 → 14/10/24

Keywords

Dot/dash line detection
Large scale image
Local image domain analysis
Parallel layer scanning
Processing time reduction

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-11758-4_43

Fingerprint Dive into the research topics of 'Parallel layer scanning based fast dot/dash line detection algorithm for large scale binary document images'. Together they form a unique fingerprint.

Cite this

Premachandra, C., Premachandra, H. W. H., Parape, C. D., & Kawanaka, H. (2014). Parallel layer scanning based fast dot/dash line detection algorithm for large scale binary document images. In M. Kamel, & A. Campilho (Eds.), Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings (pp. 395-402). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8814). Springer Verlag. https://doi.org/10.1007/978-3-319-11758-4_43

Parallel layer scanning based fast dot/dash line detection algorithm for large scale binary document images. / Premachandra, Chinthaka; Premachandra, H. Waruna H.; Parape, Chandana D.; Kawanaka, Hiroharu.

Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings. ed. / Mohamed Kamel; Aurélio Campilho. Springer Verlag, 2014. p. 395-402 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8814).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Premachandra, C, Premachandra, HWH, Parape, CD & Kawanaka, H 2014, Parallel layer scanning based fast dot/dash line detection algorithm for large scale binary document images. in M Kamel & A Campilho (eds), Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8814, Springer Verlag, pp. 395-402, 11th International Conference on Image Analysis and Recognition, ICIAR 2014, Vilamoura, Portugal, 14/10/22. https://doi.org/10.1007/978-3-319-11758-4_43

Premachandra C, Premachandra HWH, Parape CD, Kawanaka H. Parallel layer scanning based fast dot/dash line detection algorithm for large scale binary document images. In Kamel M, Campilho A, editors, Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings. Springer Verlag. 2014. p. 395-402. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-11758-4_43

Premachandra, Chinthaka ; Premachandra, H. Waruna H. ; Parape, Chandana D. ; Kawanaka, Hiroharu. / Parallel layer scanning based fast dot/dash line detection algorithm for large scale binary document images. Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings. editor / Mohamed Kamel ; Aurélio Campilho. Springer Verlag, 2014. pp. 395-402 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{d5ccdd6596ad4d34b4a6fe3a89830f4c,

title = "Parallel layer scanning based fast dot/dash line detection algorithm for large scale binary document images",

abstract = "A fast dot/dash line detection method suitable for large scale binary document images is proposed. The method works by reducing the number of scanned pixels used for the detection process. In the new method, pixels in vertical image layers with only a constant spacing are scanned. By using this technique, the computational time can be reduced because some of the uninteresting objects in the image can easily be omitted in the scanning stage. The new method is faster than the conventional method not only due to its scanning method but it also due to the simple process used for detecting dot/dash lines. A dot/dash line is detected by selecting a small defined image domain from the large scale image. We evaluated the new method against conventional methods on appropriate document images and found an improved processing time without any significant loss of line detection ability.",

keywords = "Dot/dash line detection, Large scale image, Local image domain analysis, Parallel layer scanning, Processing time reduction",

author = "Chinthaka Premachandra and Premachandra, {H. Waruna H.} and Parape, {Chandana D.} and Hiroharu Kawanaka",

year = "2014",

month = jan,

day = "1",

doi = "10.1007/978-3-319-11758-4_43",

language = "English",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "395--402",

editor = "Mohamed Kamel and Aur{\'e}lio Campilho",

booktitle = "Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings",

note = "11th International Conference on Image Analysis and Recognition, ICIAR 2014 ; Conference date: 22-10-2014 Through 24-10-2014",

}

TY - GEN

T1 - Parallel layer scanning based fast dot/dash line detection algorithm for large scale binary document images

AU - Premachandra, Chinthaka

AU - Premachandra, H. Waruna H.

AU - Parape, Chandana D.

AU - Kawanaka, Hiroharu

PY - 2014/1/1

Y1 - 2014/1/1

N2 - A fast dot/dash line detection method suitable for large scale binary document images is proposed. The method works by reducing the number of scanned pixels used for the detection process. In the new method, pixels in vertical image layers with only a constant spacing are scanned. By using this technique, the computational time can be reduced because some of the uninteresting objects in the image can easily be omitted in the scanning stage. The new method is faster than the conventional method not only due to its scanning method but it also due to the simple process used for detecting dot/dash lines. A dot/dash line is detected by selecting a small defined image domain from the large scale image. We evaluated the new method against conventional methods on appropriate document images and found an improved processing time without any significant loss of line detection ability.

AB - A fast dot/dash line detection method suitable for large scale binary document images is proposed. The method works by reducing the number of scanned pixels used for the detection process. In the new method, pixels in vertical image layers with only a constant spacing are scanned. By using this technique, the computational time can be reduced because some of the uninteresting objects in the image can easily be omitted in the scanning stage. The new method is faster than the conventional method not only due to its scanning method but it also due to the simple process used for detecting dot/dash lines. A dot/dash line is detected by selecting a small defined image domain from the large scale image. We evaluated the new method against conventional methods on appropriate document images and found an improved processing time without any significant loss of line detection ability.

KW - Dot/dash line detection

KW - Large scale image

KW - Local image domain analysis

KW - Parallel layer scanning

KW - Processing time reduction

UR - http://www.scopus.com/inward/record.url?scp=84908676064&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84908676064&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-11758-4_43

DO - 10.1007/978-3-319-11758-4_43

M3 - Conference contribution

AN - SCOPUS:84908676064

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 395

EP - 402

BT - Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings

A2 - Kamel, Mohamed

A2 - Campilho, Aurélio

PB - Springer Verlag

T2 - 11th International Conference on Image Analysis and Recognition, ICIAR 2014

Y2 - 22 October 2014 through 24 October 2014

ER -