Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)

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A Machine Learning Based Approach for Image Quality Assessment of Forged Document Images

Authors
Gayatri Patil1, 1, *, Shivanand S. Gornale1, Ashvini Babaleshwar2
1Department of Computer Science, Rani Channamma University, Belagavi, India
2Department of Computer Science, Garden City University, Bangalore, India
*Corresponding author. Email: gayatripatil865@gmail.com
Corresponding Author
Gayatri Patil
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-196-8_18How to use a DOI?
Keywords
Document Forgery; Image Quality Measures; Multiple forgery operations; Random Forest tree; Ten Class Classification
Abstract

Document Images, such as typed and handwritten documents can be manipulated in various ways using many sophisticated digital technologies and photo editing software’s. As a result, one can alter the text in the typed and handwritten documents that leads to degradation of quality of an image. The detection of multiple inherently altering operations in an image is a challenging issue, hence in this work a novel approach is proposed for the ten-class problem in which the alteration of a text can be accomplished through multiple operations, which all create the specific pattern. These operations are analysed with the help of image quality measures and classified using random forests classifier. The proposed approach gives a better classification accuracy rate of 94% for forged printed document images and 98.80% of forged handwritten document images, which is more promising and competitive with state of the art techniques reported in the literature.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
Series
Advances in Intelligent Systems Research
Publication Date
10 August 2023
ISBN
978-94-6463-196-8
ISSN
1951-6851
DOI
10.2991/978-94-6463-196-8_18How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Gayatri Patil
AU  - Shivanand S. Gornale
AU  - Ashvini Babaleshwar
PY  - 2023
DA  - 2023/08/10
TI  - A Machine Learning Based Approach for Image Quality Assessment of Forged Document Images
BT  - Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
PB  - Atlantis Press
SP  - 208
EP  - 229
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-196-8_18
DO  - 10.2991/978-94-6463-196-8_18
ID  - Patil2023
ER  -