Counting Pixels for an Effective Axis Detection

Keeheon Lee; Eury Sohn; Kunhee Ryu; Seongmin Oh

doi:10.1109/IRI54793.2022.00041

Counting Pixels for an Effective Axis Detection

Keeheon Lee, Eury Sohn, Kunhee Ryu, Seongmin Oh

Techno-Art Division

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

Abstract

To examine the charts critically and to synthesize the charts across relevant papers in a large-scale accessible digitally, we need an efficient way to extract data from visual information in the charts. Axis detection is the crux in such data extraction from the charts. Thus, we introduce a rule-based axis detection algorithm that is computationally less expensive and more accurate by using simple pixel counting.

Original language	English
Title of host publication	Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	144-145
Number of pages	2
ISBN (Electronic)	9781665466035
DOIs	https://doi.org/10.1109/IRI54793.2022.00041
Publication status	Published - 2022
Event	23rd IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2022 - Virtual, Online, United States Duration: 2022 Aug 9 → 2022 Aug 11

Publication series

Name	Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022

Conference

Conference	23rd IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2022
Country/Territory	United States
City	Virtual, Online
Period	22/8/9 → 22/8/11

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Science Applications
Computer Vision and Pattern Recognition
Decision Sciences (miscellaneous)
Information Systems and Management
Safety, Risk, Reliability and Quality

Access to Document

10.1109/IRI54793.2022.00041

Cite this

Lee, K., Sohn, E., Ryu, K., & Oh, S. (2022). Counting Pixels for an Effective Axis Detection. In Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022 (pp. 144-145). (Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IRI54793.2022.00041

Lee, Keeheon ; Sohn, Eury ; Ryu, Kunhee et al. / Counting Pixels for an Effective Axis Detection. Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 144-145 (Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022).

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title = "Counting Pixels for an Effective Axis Detection",

abstract = "To examine the charts critically and to synthesize the charts across relevant papers in a large-scale accessible digitally, we need an efficient way to extract data from visual information in the charts. Axis detection is the crux in such data extraction from the charts. Thus, we introduce a rule-based axis detection algorithm that is computationally less expensive and more accurate by using simple pixel counting.",

keywords = "Axis Detection, Computer Vision, Data Extraction",

author = "Keeheon Lee and Eury Sohn and Kunhee Ryu and Seongmin Oh",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 23rd IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2022 ; Conference date: 09-08-2022 Through 11-08-2022",

year = "2022",

doi = "10.1109/IRI54793.2022.00041",

language = "English",

series = "Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022",

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

pages = "144--145",

booktitle = "Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022",

address = "United States",

}

Lee, K, Sohn, E, Ryu, K & Oh, S 2022, Counting Pixels for an Effective Axis Detection. in Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022. Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022, Institute of Electrical and Electronics Engineers Inc., pp. 144-145, 23rd IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2022, Virtual, Online, United States, 22/8/9. https://doi.org/10.1109/IRI54793.2022.00041

Counting Pixels for an Effective Axis Detection. / Lee, Keeheon; Sohn, Eury; Ryu, Kunhee et al.
Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 144-145 (Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022).

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

TY - GEN

T1 - Counting Pixels for an Effective Axis Detection

AU - Lee, Keeheon

AU - Sohn, Eury

AU - Ryu, Kunhee

AU - Oh, Seongmin

PY - 2022

Y1 - 2022

N2 - To examine the charts critically and to synthesize the charts across relevant papers in a large-scale accessible digitally, we need an efficient way to extract data from visual information in the charts. Axis detection is the crux in such data extraction from the charts. Thus, we introduce a rule-based axis detection algorithm that is computationally less expensive and more accurate by using simple pixel counting.

AB - To examine the charts critically and to synthesize the charts across relevant papers in a large-scale accessible digitally, we need an efficient way to extract data from visual information in the charts. Axis detection is the crux in such data extraction from the charts. Thus, we introduce a rule-based axis detection algorithm that is computationally less expensive and more accurate by using simple pixel counting.

KW - Axis Detection

KW - Computer Vision

KW - Data Extraction

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U2 - 10.1109/IRI54793.2022.00041

DO - 10.1109/IRI54793.2022.00041

M3 - Conference contribution

AN - SCOPUS:85139084886

T3 - Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022

SP - 144

EP - 145

BT - Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 23rd IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2022

Y2 - 9 August 2022 through 11 August 2022

ER -

Lee K, Sohn E, Ryu K, Oh S. Counting Pixels for an Effective Axis Detection. In Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 144-145. (Proceedings - 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science, IRI 2022). doi: 10.1109/IRI54793.2022.00041

Counting Pixels for an Effective Axis Detection

Abstract

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Bibliographical note

All Science Journal Classification (ASJC) codes

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