The Industrial Application of Artificial Intelligence-Based Optical Character Recognition in Modern Manufacturing Innovations

Qing Tang, YoungSeok Lee and Hail Jung ()
Additional contact information
Qing Tang: Data Science Group, INTERX, Ulsan 44542, Republic of Korea
YoungSeok Lee: Data Science Group, INTERX, Ulsan 44542, Republic of Korea
Hail Jung: Department of Business Administration, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea

Sustainability, 2024, vol. 16, issue 5, 1-20

Abstract: This paper presents the development of a comprehensive, on-site industrial Optical Character Recognition (OCR) system tailored for reading text on iron plates. Initially, the system utilizes a text region detection network to identify the text area, enabling camera adjustments along the x and y axes and zoom enhancements for clearer text imagery. Subsequently, the detected text region undergoes line-by-line division through a text segmentation network. Each line is then transformed into rectangular patches for character recognition by the text recognition network, comprising a vision-based text recognition model and a language network. The vision network performs preliminary recognition, followed by refinement through the language model. The OCR results are then converted into digital characters and recorded in the iron plate registration system. This paper’s contributions are threefold: (1) the design of a comprehensive, on-site industrial OCR system for autonomous registration of iron plates; (2) the development of a realistic synthetic image generation strategy and a robust data augmentation strategy to address data scarcity; and (3) demonstrated impressive experimental results, indicating potential for on-site industrial applications. The designed autonomous system enhances iron plate registration efficiency and significantly reduces factory time and labor costs.

Keywords: artificial intelligence; optical character recognition; manufacturing innovation; manufacturing industrial; real-world application (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/5/2161/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/5/2161/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:5:p:2161-:d:1351692

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().