In addition to ensuring image authenticity, watermarking aids in the recovery of digital images that have been altered or tampered with during transmission. Although many techniques have been developed for embedding the watermark that results in recovering itself of photos, they only effectively work in the uncompressed multiple domains, leaving images vulnerable to attacks on image compression, such as noise addition. In order to effectively detect tampered areas and assure self-recovery of JPEG images, we offer a solution to address these issues in the JPEG domain. Source code compresses the original image, while channel code protects it from tampering. As a result, the image will be compressed and then used as the watermark which is embedded. The approach proposed is successfully combined with these JPEG images, producing increased image quality as well as strong performance against noise attacks.

1. Dr. M. T. Somashekara
Associate Professor,
Department of Computer Science and
Applications,
Bangalore University, Bengaluru, India.
Under the Guidance of,
Pavan. A. C
Research Scholar,
Department of Computer Science and
Applications,
Bangalore University, Bengaluru, India.
Presented By,
An Approach for Detecting and Restoring
Tampering in Digital Image Watermarking
5th International Conference on Cognitive Computing and
Information Processing (CCIP 2023)

2. 5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023
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L I T E R A T U R E S U R V E Y
I N T R O D U C T I O N
E X P E R I M E N T A L R E S U L T S
M E T H O D O L O G Y
C O N C L U S I O N
R E F E R E N C E S
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3. Introduction
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 3

4. What is Digital
Image
Watermarking?
• Digital image watermarking is a technique used to embed
information, often in the form of a digital watermark or a
code, into a digital image.
• The purpose of digital image watermarking is to provide a
way to verify the authenticity or ownership of an image,
protect against unauthorized use, and track the
distribution of digital media.
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 4

5. • Proposed method defines the tampering
as a source coding problem and hence
develop a watermark which could help in
self-recovery of the tampered image.
• The method includes compressing the
original image by source coding using
SPIHT algorithm.
Tamper Detection
with JPEG
Compression
Tamper Detection
with LSB-MSB
• Replace each image block's least significant
bits (LSB) with bits generated from that
block's most significant bits (MSB)
• These methods are ineffective against noise
assaults
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 5

6. Literature
Survey
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 6

7. Literature Survey
2011
Z. Qian, G. Feng,
Inpainting assisted
self-recovery with
decreased embedding
data.
J. Fridrich, et. al The
DCT values which
were quantized along
with the version
generated by low
depth of the original
image can be used as
important features for
generating.
1999
S. Sarreshtedari,
M.A. Akhaee, Source-
channel coding
approach to generate
tamperproof images.
2014
P. Korus, J. Biaas, A.
Dziech, Towards
practical self-
embedding for JPEG-
compressed digital
images.
2015
Saeed Sarreshtedari,
et. al Source-channel
coding-based
watermarking for self-
embedding of JPEG
images.
2017
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 7

8. Methodology
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 8

9. Embedding
Algorithm
Sender Side
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 9

10. Embedding
Algorithm
Receiver Side
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 10

11. Algorithms
with
Methodology
Compression of Lossy Data
DCT is applied to compress the image
SPIHT
Used for source coding
LDPC Codes
Channel coding algorithm to detect the
error and make the recovery
Embedding of Watermark
Watermark will be embedded bit by bit
Restoration of an Image
Identify the manipulated bits
Tampering Detection
Comparing and detection of tamper
using Thresholding, erosion and dilation
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 1

12. Experimental
Results
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 1

13. Tampering Rate 15%-17%
Tampering
Original image may be
restored by the proposed
method as long as the
tampering and these
additional attacks leads to
tampering of the watermarked
image within 17.2%.
Image Size
Proposed scheme is tested on
8-bit 512 × 512 grey-scale
image
Attacks
The results are robust against
the attacks such as noise
addition and recompression
on the received image along
with tampering.
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 13

14. 5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023
Original Image Tampered Image
Compressed Image
Image Representation
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15. 5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023
Thresholding and opening
Result
Tampering Map Recovered Image
Image Representation
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16. Conclusion
5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023 16

17. 5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023
A tamper proof watermark embedding process has been
proposed in this paper.
A tamper proof watermark embedding process has been
adapted suitably with respect to the standard JPEG
compression chain.
Since, compression reduces the redundancy of image and
available capacity for watermark embedding is limited, the
recovery of tampering is also up to certain tolerable rate.
Recovery of the original image significantly depends on size
of the watermark string embedded into it.
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18. References
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19. 5th International Conference on Cognitive Computing and Information Processing (CCIP 2023) 15th & 16th DEC 2023
• Saeed Sarreshtedari, Mohammad Ali Akhaee, AliazamAbbasfar, "Source-channel coding-based
watermarking for self-embedding of JPEG images", Electrical and Computer Engg., University
of Tehran, 2017, pp 107-116
• J. Fridrich, M. Goljan, (1999) Images with self-correcting capabilities, in: Proc. Int. Conf. on
Image Processing, Vol. 3, pp. 792–796
• Z. Qian, G. Feng, Inpainting assisted self-recovery with decreased embedding data, IEEEFigure
6 Received tampered image X. Zhang, Z. Qian, Y. Ren, G. Feng, Watermarking with flexible self-
recovery quality based on compressive sensing and compositive reconstruction, IEEE Trans.
Inform.Forensics Secur. 6 (4) (2011) 1223–1232.
• P. Korus, J. Biaas, A. Dziech, Towards practical self-embedding for JPEG-compressed digital
images, IEEE Trans. Multimedia 17 (2) (2015) 157–170.
http://dx.doi.org/10.1109/TMM.2014.2368696.
• S. Sarreshtedari, M.A. Akhaee, A source-channel coding approach to digital image protection
and self-recovery, IEEE Trans. Image Process. 24 (7) (2015) 2266–2277.
• S. Sarreshtedari, M.A. Akhaee, Source-channel coding approach to generate tamperproof
images, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
2014, pp. 7435– 7439, doi:10.1109/ICASSP.2014.6855045.
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20. Thank You..!