Data-Hiding and Compression Schema Based on Image Inpainting

Authors

  • Akilashri PSS Department of Computer Science,National College, Tiruchirappalli, India
  • Kannan BM RKV Matric Hr Sec School Jedarpalayam, Tamil Nadu, India

Keywords:

Image Compression, Side Match Vector Quantization (SMVQ), Data Hiding, Image In Painting

Abstract

Digital images and videos are converted into the compressed forms for transmission. The compression and hiding the secret data in images is done because of a wide range of hackers. In order to overcome this, the messages are sent with the help of images. Many data hiding schemes have been found in the recent times with various compression techniques in digital images. Vector Quantization method help in error distortion and error diffusion which are a cause of progressive diffusion. The new idea is that one can side match vector quantization (SMVQ) and image inpainting. Data hiding and image compression can be integrated into a single module to sent the message. The receiver then finds the secret message using the image decompression technique through the index values in the segmented sections

References

[1] H. W. Tseng and C. C. Chang, “High capacity data hiding in JPEGcompressed images,” Informatica, vol. 15, no. 1, pp.127–142, 2004

[2] D. S. Taubman and M. W. Marcellin, JPEG2000: Image Compression Fundamentals Standards and Practice. Norwell, MA, USA: Kluwer, 2002.

[3] A. Gersho and R. M. Gray, Vector Quantization and Signal Compression. Norwell, MA, USA: Kluwer, 1992.

[4] N. M. Nasrabadi and R. King, “Image coding using vector quantization: A review,” IEEE Trans. Commun., vol. 36, no. 8, pp. 957–971, Aug. 1988.

[5] Announcing the Advanced Encryption Standard (AES), National Institute of Standards & Technology, Gaithersburg, MD, USA, Nov. 2001.

[6] R. L. Rivest, A. Shamir, and L. Adleman, “A method for obtaining digital signatures and public-key cryptosystems,” Commun.ACM, vol. 21, no. 2, pp. 120–126, 1978.

[7] F. A. P. Petitcolas, R. J. Anderson, and M. G. Kuhn, “Information hiding survey,” Proc. IEEE, vol. 87, no. 7, pp. 1062 –1078, Jul. 1999.

[8] C. D. Vleeschouwer, J. F. Delaigle, and B Macq, “Invisibility and application functionalities in perceptual watermarking: An overview,” Proc. IEEE, vol. 90, no. 1, pp. 64–77, Jan. 2002.

[9] C. C. Chang, T. S. Chen, and L. Z. Chung, “A steganographic method based upon JPEG and quantization table modification,” Inf. Sci., vol. 141, no. 1, pp. 123–138, 2002

[10] W. B. Pennebaker and J. L. Mitchell, The JPEG Still Image Data Compression Standard. New York, NY, USA: Reinhold, 1993

Downloads

Published

2025-11-18

How to Cite

[1]
P. Akilashri and B. Kannan, “Data-Hiding and Compression Schema Based on Image Inpainting”, Int. J. Comp. Sci. Eng., vol. 6, no. 11, pp. 243–245, Nov. 2025.

Issue

Vol. 6 No. 11 (2018): IJCSE Special Issue December Edition

Section

Survey Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.