A Robust Digital Image Watermarking Technique Against Geometrical Attacks Using Support Vector Machine and Glowworm Optimization

  • Parmalik KumarEmail author
  • A. K. Sharma
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 38)


The tampering and forgery of digital multimedia data remains as one of the most important challenges all over the internet. Digital image watermarking techniques are used to overcome these challenges. The digital image watermarking techniques provides the security for multimedia data. In this paper, discuss the image features optimization-based digital image watermarking algorithm. The proposed algorithm prevents geometrical attacks during the transmission of data. The proposed algorithm uses support vector machine and glowworm optimization algorithms. The support vector machine classifies the features data of raw image and glowworm optimization used for the reduction cum selection of features for the proceeds of embedded for the extraction of features used SIFT (scale-invariant feature transform) function. The scale-invariant feature transform is major dominated features of critical points and features points. The proposed algorithm implemented in MATLAB software. For the validation and testing purpose used 300 image dataset. For the evaluation of performance measure, these parameters such as PSNR, NC, and SIM. The measured results show better performance instead of SIFT and SVM-GA.


Attacks GA GSO SIFT SVM Transform function Watermarking 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Shri Venkateshwara UniversityGajraulaIndia

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