Template-based text field segmentation for ID documents using dynamic squeezeboxes packing.
Saved in:
| Title: | Template-based text field segmentation for ID documents using dynamic squeezeboxes packing. |
|---|---|
| Authors: | Zingerenko, Michael1,2 (AUTHOR) zingerenko.mv@phystech.edu, Limonova, Elena2,3 (AUTHOR) limonova@smartengines.com, Arlazarov, Vladimir V.2,3 (AUTHOR) vva@smartengines.com |
| Source: | Multimedia Tools & Applications. Jul2025, Vol. 84 Issue 23, p27311-27325. 15p. |
| Subjects: | Identification documents, Document imaging systems, Algorithms, Packing problem (Mathematics), Computer performance |
| Abstract: | In this paper, we focus on the problem of text field segmentation in identity documents. These documents, characterized by their fixed layouts, present an opportunity to apply computationally efficient template-based algorithms. We consider the Dynamic Squeezeboxes Packing method and demonstrate its integration into document recognition systems, utilizing a single sample per document type. We benchmark text field segmentation on the MIDV-2019 public dataset using standard intersection-over-union and our custom intersection-over-template metrics, while also measuring processing time. We demonstrate that Dynamic Squeezeboxes Packing maintains competitive quality compared to text in the wild methods (EAST, CRAFT) and named-entity recognition method (LayoutLMv2). A significant advantage of this method is its processing speed, averaging 9 ms per image on the x86_64 platform, which is substantially faster than EAST (980 ms), CRAFT (2030 ms), and LayoutLMv2 (2210 ms). The obtained results suggest that the considered method has strong potential as a method in document image analysis, particularly for processing identity documents. [ABSTRACT FROM AUTHOR] |
| Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 186712559 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Template-based text field segmentation for ID documents using dynamic squeezeboxes packing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zingerenko%2C+Michael%22">Zingerenko, Michael</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> zingerenko.mv@phystech.edu</i><br /><searchLink fieldCode="AR" term="%22Limonova%2C+Elena%22">Limonova, Elena</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> limonova@smartengines.com</i><br /><searchLink fieldCode="AR" term="%22Arlazarov%2C+Vladimir+V%2E%22">Arlazarov, Vladimir V.</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> vva@smartengines.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>. Jul2025, Vol. 84 Issue 23, p27311-27325. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Identification+documents%22">Identification documents</searchLink><br /><searchLink fieldCode="DE" term="%22Document+imaging+systems%22">Document imaging systems</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Packing+problem+%28Mathematics%29%22">Packing problem (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+performance%22">Computer performance</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In this paper, we focus on the problem of text field segmentation in identity documents. These documents, characterized by their fixed layouts, present an opportunity to apply computationally efficient template-based algorithms. We consider the Dynamic Squeezeboxes Packing method and demonstrate its integration into document recognition systems, utilizing a single sample per document type. We benchmark text field segmentation on the MIDV-2019 public dataset using standard intersection-over-union and our custom intersection-over-template metrics, while also measuring processing time. We demonstrate that Dynamic Squeezeboxes Packing maintains competitive quality compared to text in the wild methods (EAST, CRAFT) and named-entity recognition method (LayoutLMv2). A significant advantage of this method is its processing speed, averaging 9 ms per image on the x86_64 platform, which is substantially faster than EAST (980 ms), CRAFT (2030 ms), and LayoutLMv2 (2210 ms). The obtained results suggest that the considered method has strong potential as a method in document image analysis, particularly for processing identity documents. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=186712559 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-024-20162-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 27311 Subjects: – SubjectFull: Identification documents Type: general – SubjectFull: Document imaging systems Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Packing problem (Mathematics) Type: general – SubjectFull: Computer performance Type: general Titles: – TitleFull: Template-based text field segmentation for ID documents using dynamic squeezeboxes packing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zingerenko, Michael – PersonEntity: Name: NameFull: Limonova, Elena – PersonEntity: Name: NameFull: Arlazarov, Vladimir V. IsPartOfRelationships: – BibEntity: Dates: – D: 11 M: 07 Text: Jul2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 84 – Type: issue Value: 23 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
| ResultId | 1 |
