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A Review on Image Encryption Technique and to Extract Feature from Image

by Samridhi Singh, H. L. Mandoria
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 163 - Number 1
Year of Publication: 2017
Authors: Samridhi Singh, H. L. Mandoria
10.5120/ijca2017913435

Samridhi Singh, H. L. Mandoria . A Review on Image Encryption Technique and to Extract Feature from Image. International Journal of Computer Applications. 163, 1 ( Apr 2017), 19-23. DOI=10.5120/ijca2017913435

@article{ 10.5120/ijca2017913435,
author = { Samridhi Singh, H. L. Mandoria },
title = { A Review on Image Encryption Technique and to Extract Feature from Image },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 163 },
number = { 1 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 19-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume163/number1/27359-2017913435/ },
doi = { 10.5120/ijca2017913435 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:08:58.203349+05:30
%A Samridhi Singh
%A H. L. Mandoria
%T A Review on Image Encryption Technique and to Extract Feature from Image
%J International Journal of Computer Applications
%@ 0975-8887
%V 163
%N 1
%P 19-23
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The security of image data from unauthorized users is important hence image encryption play an important role in hiding information. This survey paper measure up the different encryption techniques for securing multimedia data with objective to give complete review on the various encryption techniques. This paper presents a review of survey literature published from 2008 to 2015 in aspect of different image encryption/decryption techniques with tabular form and the algorithms used to extract the features from the images.

References
  1. Mohammad Ali Bani Younes et al (2008) “Image Encryption Using Block-Based Transformation Algorithm” IAENG International Journal of Computer Science.
  2. Mohammad Ali Bani Younes et al(April 2008), “An Image Encryption Approach Using a Combination of Permutation Technique Followed by Encryption”, IJCSNS International Journal of Computer Science and Network Security
  3. . Amitava Nag et al (2011)”Image Encryption Using Affine Transform and XOR Operation”, InternationalConference on Signal Processing, Communication, Computing and Networking Technologies (ICSCCN).
  4. Rasul Enayatifar et al(2011)” Image Security via Genetic Algorithm”, International Conference on Computer and Software Modeling IPCSIT vol.14
  5. Sukalyan Som et al (2012)” Confusion and Diffusion of Grayscale Images Using Multiple Chaotic Maps”, National Conference on Computing and Communication Systems (NCCCS).
  6. Pia Singh et al (July-2013) "Image Encryption and Decryption Using Blowfish Algorithm in Matlab," International Journal of Scientific & Engineering Research, vol. 4, Issue. 7.
  7. P. S. Ghode, (May 2014) “A Keyless approach to Lossless Image Encryption”, International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE.), vol. 4, Issue. 5, pp. 1459- 1467.
  8. W. Zhu, (2014) "Image Encryption using CAT Mapping and Chaos Approach," International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 7, no. 3, pp.1-8.
  9. A. Jain et al (February 2015) "A robust image encryption algorithm resistant to attacks using DNA and chaotic logistic maps," Multimedia Tools and Applications, An International Journal, Springer Science + Business Media Ne Yourk, pp. 1-18.
  10. A. Devi et al (2015) "A Review on DES, AES and Blowfish for Image Encryption & Decryption,” (IJCSIT) International Journal of Computer Science and Information Technologies, vol. 6, Issue. 3, pp. 3034-3036. http://www.ijcsit.com.
  11. Liang Zhao et al (2012) “On the security analysis of an image scrambling encryption of pixel bit and its improved scheme based on self-correlation encryption”, Communications in Nonlinear Science and Numerical Simulation, Vol. 17, No. 8, pp3303-3327.
  12. G.A. Sathishkumar et al (2011) “A novel image encryption algorithm using pixel shuffling and BASE 64 encoding based chaotic block cipher, WSEAS Transactions on Computers, Vol. 10, No. 6, pp169-178.
  13. Jinxia L et al, “Application of SIFT feature extraction algorithm on the image registration”. In: Tenth international conference on electronic measurement & instruments IEEE.
  14. Lowe D., (2004) “Distinctive image features from scale-invariant key points”. IJCV 2004; 60(2):91–110.
  15. Wang X., “Robust image retrieval based on color histogram of local feature regions”. Springer Netherlands; 2009.
  16. Stokman H et al, (March 2008)” Selection and fusion of color models for image feature detection”. Pattern Anal Mach Intel IEEE Trans; 29:371–81.
  17. Rosen E et al, (2010) “FASTER and better: a machine learning approach to corner detection”. IEEE Trans Pattern Anal Mach Intel; 32:105–19.
  18. D. Zhang et al,( 2004) “Review of shape representation and description techniques”, Pattern Recognition, vol. 37, no. 1, pp. 1-19.
  19. L. Li et al, (2012) "Texture Classification from Random Features," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 3, pp. 574-586.
  20. M. K. Swain et al (1991.) "Color indexing". International Journal of Computer Vision, vol. 7, no. 1, pp. 11-32.
  21. Rosten E et al (2010) “FASTER and better: a machine learning approach to corner detection”. IEEE Trans Pattern Anal Mach Intel; 32:105–19.
  22. D. P. Tian et al (2013) “A Review on Image Feature Extraction and Representation”, Techniques International Journal of Multimedia and Ubiquitous Engineering, vol. 8, no. 4, pp. 385-396.
  23. Sonal Paliwal et al,( June 2016)”A survey on various Text Detection and Extraction technique from videos and images”. IJCSEITR
  24. Bhomika Pandey et al, “A Comprehensive study on text and image stenography”, IJETTCS, February 2016.
  25. Navneet kr. Kashyap et al, (may 2016)”Analysis of pattern identification using graph database for fraud detection”,, OJCST.
  26. Poonam Singh et al (Sep 2015)” Performance analysis of image and video coding by Wavelet Transform Using Region of interest”, IJERMT.
  27. Dixcha Gusain et al, (January 2016) ” Comparative analysis of filters for extraction from noisy images”, IJESRT.
Index Terms

Computer Science
Information Sciences

Keywords

Encryption feature extraction color texture algorithms.the correlation between image elements was significantly decreased. Results also show that increasing the number of blocks by using smaller block sizes resulted in a lower correlation and higher entropy [1]. An Image Encryption Approach Using a Combination of Permutation Technique Followed by Encryption: It is a new permutation technique based on the combination of image permutation and a well known encryption algorithm called RijnDael. The original image was divided into 4×4 pixels blocks which were repositioned into a permuted image using a permutation process and then the generated image was encrypted using the RijnDael algorithm [2]. Younes results show that the connection between image elements was significantly decreased by using the combination technique and higher entropy was attained.

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