Forensic image reconstruction based on efficient morphological operational model

Sajib Bhawal; Mehnaz Tabassum

doi:10.1007/978-981-13-1501-5_26

Forensic image reconstruction based on efficient morphological operational model

Sajib Bhawal, Mehnaz Tabassum

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

1 Citation (Scopus)

Abstract

Fragmented forensic image recovering from unallocated space plays an important role in computer forensics and investigation. For clear-cut investigation, it is necessary to reconstruct the recovered forensic images. Morphological operations can reconstruct the recovered images. Existing paper applies different methods to a damaged image based on structuring element, but cannot recuperate damaged image properly. This paper proposed a morphological image processing model that applies some operations like H-maxima transform, bottom-hat transformation, erosion, opening, dilation, closing operations based on structuring elements to sharp the final output image. This model can fill all holes of the damaged image properly compared to reference model. Structural Similarity Index (SSIM), Peak Signal-to-Noise Ratio (PSNR) of the proposed model is higher than the reference model. This paper applies security mechanism such as watermarking with Discrete Cosine Transform (DCT) to hide the image in the forensic workstation.

Original language	English
Title of host publication	Emerging technologies in data mining and information security
Subtitle of host publication	proceedings of IEMIS 2018
Editors	Ajith Abraham, Paramartha Dutta, Jyotsna Kumar Mandal, Abhishek Bhattacharya, Soumi Dutta
Place of Publication	Singapore
Publisher	Springer-VDI-Verlag GmbH & Co. KG
Pages	297-307
Number of pages	11
Volume	3
ISBN (Electronic)	9789811315015
ISBN (Print)	9789811315008
DOIs	https://doi.org/10.1007/978-981-13-1501-5_26
Publication status	Published - 2019
Externally published	Yes
Event	International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2018 - Kolkata, India Duration: 23 Feb 2018 → 25 Feb 2018

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
Volume	814
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2018
Country/Territory	India
City	Kolkata
Period	23/02/18 → 25/02/18

Keywords

Bottom-hat transformation
Carving
DCT
Forensics
H-maxima transform
Morphological processing
PSNR
SSIM
Top-hat transformation

Access to Document

10.1007/978-981-13-1501-5_26

Cite this

Bhawal, S., & Tabassum, M. (2019). Forensic image reconstruction based on efficient morphological operational model. In A. Abraham, P. Dutta, J. K. Mandal, A. Bhattacharya, & S. Dutta (Eds.), Emerging technologies in data mining and information security: proceedings of IEMIS 2018 (Vol. 3, pp. 297-307). (Advances in Intelligent Systems and Computing; Vol. 814). Springer-VDI-Verlag GmbH & Co. KG. https://doi.org/10.1007/978-981-13-1501-5_26

Bhawal, Sajib ; Tabassum, Mehnaz. / Forensic image reconstruction based on efficient morphological operational model. Emerging technologies in data mining and information security: proceedings of IEMIS 2018. editor / Ajith Abraham ; Paramartha Dutta ; Jyotsna Kumar Mandal ; Abhishek Bhattacharya ; Soumi Dutta. Vol. 3 Singapore : Springer-VDI-Verlag GmbH & Co. KG, 2019. pp. 297-307 (Advances in Intelligent Systems and Computing).

@inproceedings{4a35903155a541b6ba800d77ff70a2e2,

title = "Forensic image reconstruction based on efficient morphological operational model",

abstract = "Fragmented forensic image recovering from unallocated space plays an important role in computer forensics and investigation. For clear-cut investigation, it is necessary to reconstruct the recovered forensic images. Morphological operations can reconstruct the recovered images. Existing paper applies different methods to a damaged image based on structuring element, but cannot recuperate damaged image properly. This paper proposed a morphological image processing model that applies some operations like H-maxima transform, bottom-hat transformation, erosion, opening, dilation, closing operations based on structuring elements to sharp the final output image. This model can fill all holes of the damaged image properly compared to reference model. Structural Similarity Index (SSIM), Peak Signal-to-Noise Ratio (PSNR) of the proposed model is higher than the reference model. This paper applies security mechanism such as watermarking with Discrete Cosine Transform (DCT) to hide the image in the forensic workstation.",

keywords = "Bottom-hat transformation, Carving, DCT, Forensics, H-maxima transform, Morphological processing, PSNR, SSIM, Top-hat transformation",

author = "Sajib Bhawal and Mehnaz Tabassum",

year = "2019",

doi = "10.1007/978-981-13-1501-5\_26",

language = "English",

isbn = "9789811315008",

volume = "3",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer-VDI-Verlag GmbH \& Co. KG",

pages = "297--307",

editor = "Ajith Abraham and Paramartha Dutta and Mandal, \{Jyotsna Kumar\} and Abhishek Bhattacharya and Soumi Dutta",

booktitle = "Emerging technologies in data mining and information security",

address = "Germany",

note = "International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2018 ; Conference date: 23-02-2018 Through 25-02-2018",

}

Bhawal, S & Tabassum, M 2019, Forensic image reconstruction based on efficient morphological operational model. in A Abraham, P Dutta, JK Mandal, A Bhattacharya & S Dutta (eds), Emerging technologies in data mining and information security: proceedings of IEMIS 2018. vol. 3, Advances in Intelligent Systems and Computing, vol. 814, Springer-VDI-Verlag GmbH & Co. KG, Singapore, pp. 297-307, International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2018, Kolkata, India, 23/02/18. https://doi.org/10.1007/978-981-13-1501-5_26

Forensic image reconstruction based on efficient morphological operational model. / Bhawal, Sajib; Tabassum, Mehnaz.
Emerging technologies in data mining and information security: proceedings of IEMIS 2018. ed. / Ajith Abraham; Paramartha Dutta; Jyotsna Kumar Mandal; Abhishek Bhattacharya; Soumi Dutta. Vol. 3 Singapore: Springer-VDI-Verlag GmbH & Co. KG, 2019. p. 297-307 (Advances in Intelligent Systems and Computing; Vol. 814).

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

TY - GEN

T1 - Forensic image reconstruction based on efficient morphological operational model

AU - Bhawal, Sajib

AU - Tabassum, Mehnaz

PY - 2019

Y1 - 2019

N2 - Fragmented forensic image recovering from unallocated space plays an important role in computer forensics and investigation. For clear-cut investigation, it is necessary to reconstruct the recovered forensic images. Morphological operations can reconstruct the recovered images. Existing paper applies different methods to a damaged image based on structuring element, but cannot recuperate damaged image properly. This paper proposed a morphological image processing model that applies some operations like H-maxima transform, bottom-hat transformation, erosion, opening, dilation, closing operations based on structuring elements to sharp the final output image. This model can fill all holes of the damaged image properly compared to reference model. Structural Similarity Index (SSIM), Peak Signal-to-Noise Ratio (PSNR) of the proposed model is higher than the reference model. This paper applies security mechanism such as watermarking with Discrete Cosine Transform (DCT) to hide the image in the forensic workstation.

AB - Fragmented forensic image recovering from unallocated space plays an important role in computer forensics and investigation. For clear-cut investigation, it is necessary to reconstruct the recovered forensic images. Morphological operations can reconstruct the recovered images. Existing paper applies different methods to a damaged image based on structuring element, but cannot recuperate damaged image properly. This paper proposed a morphological image processing model that applies some operations like H-maxima transform, bottom-hat transformation, erosion, opening, dilation, closing operations based on structuring elements to sharp the final output image. This model can fill all holes of the damaged image properly compared to reference model. Structural Similarity Index (SSIM), Peak Signal-to-Noise Ratio (PSNR) of the proposed model is higher than the reference model. This paper applies security mechanism such as watermarking with Discrete Cosine Transform (DCT) to hide the image in the forensic workstation.

KW - Bottom-hat transformation

KW - Carving

KW - DCT

KW - Forensics

KW - H-maxima transform

KW - Morphological processing

KW - PSNR

KW - SSIM

KW - Top-hat transformation

UR - https://www.scopus.com/pages/publications/85053529543

U2 - 10.1007/978-981-13-1501-5_26

DO - 10.1007/978-981-13-1501-5_26

M3 - Conference proceeding contribution

SN - 9789811315008

VL - 3

T3 - Advances in Intelligent Systems and Computing

SP - 297

EP - 307

BT - Emerging technologies in data mining and information security

A2 - Abraham, Ajith

A2 - Dutta, Paramartha

A2 - Mandal, Jyotsna Kumar

A2 - Bhattacharya, Abhishek

A2 - Dutta, Soumi

PB - Springer-VDI-Verlag GmbH & Co. KG

CY - Singapore

T2 - International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2018

Y2 - 23 February 2018 through 25 February 2018

ER -

Bhawal S, Tabassum M. Forensic image reconstruction based on efficient morphological operational model. In Abraham A, Dutta P, Mandal JK, Bhattacharya A, Dutta S, editors, Emerging technologies in data mining and information security: proceedings of IEMIS 2018. Vol. 3. Singapore: Springer-VDI-Verlag GmbH & Co. KG. 2019. p. 297-307. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-981-13-1501-5_26

Forensic image reconstruction based on efficient morphological operational model

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this