Development of a cropping resilient watermarking scheme based on contourlet transform for secure IoT communication




contourlet transform, watermarking, Arnold transform, geometric attacks, cropping attack, SVD


The objective of this work is to propose a robust watermarking method as watermarking techniques are widely used today for preventing image altering and duplication. With the growth of image-based IoT applications nowadays, the need for developing robust digital watermarking techniques is of high demand. In this work, a robust yet highly perceptible watermarking scheme is proposed. The proposed scheme is based on the Contourlet Transform (CT) and Singular Value Decomposition (SVD) as the embedding domain in which the high-frequency components are chosen for embedding. The frequency domain is selected in order to make the watermarking scheme resists image attacks as the watermark is spreaded across different frequency bands in the cover image and hence the possibility of altering all the embedded bands is not possible as it will results in destroying the cover image. On the other hand, the Arnold transformation was used to insure secure IOT communication where the Arnold transform is applied to the binary logo watermark before embedding for a more secure design. In this context, the host image has been decomposed into the first level of contourlet transform and the highest frequency sub-bands are selected for embedding after performing the SVD on those bands where the SVD matrix is chosen to be the embedding domain. Moreover, This work aims to resist the cropping attack on images where PSNR values were above 52 dB and NC values ranged from 0.8 to 0.9 under various types of cropping attacks. In addition, the proposed method demonstrates its ability to resist various geometric and noise attacks such as JPEG compression, histogram equalization, gaussian noising and image brightening. Comparisons with state-of-the-art work demonstrate the proposed scheme's efficienc

Author Biographies

Yahya Idham, Ninevah University


Department of Computers and Information

College of Electronics Engineering

Omar Alsaydia, Ninevah University

Master of Science in Computer Network, Assistant Lecturer

Department of Computer and Information

College of Electronics Engineering

Mohammed A. M. Abdullah, Ninevah University


Department of Computer and Information Engineering

College of Electronics Engineering

Ahmed Mohammed, Ninevah University

Lecturer, Master

Department of Computer and Information

College of Electronics Engineering

Ersin Elbasi, College of Engineering and Technology American University of the Middle East



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Development of a cropping resilient watermarking scheme based on contourlet transform for secure IoT communication




How to Cite

Idham, Y., Alsaydia, O., Abdullah, M. A. M., Mohammed, A., & Elbasi, E. (2023). Development of a cropping resilient watermarking scheme based on contourlet transform for secure IoT communication. Eastern-European Journal of Enterprise Technologies, 1(2 (121), 21–28.