JOURNAL ARTICLE

Firefly optimized robust, imperceptible, secure watermarking scheme

S. S. AgrawalA. S. Bhalchandra

Year: 2022 Journal:   Indonesian Journal of Electrical Engineering and Computer Science Vol: 28 (2)Pages: 1155-1155   Publisher: Institute of Advanced Engineering and Science (IAES)

Abstract

A multi-objective optimized hybrid image watermarking technique is being proposed considering robustness, imperceptibility and security aspects using two different scaling factors. In this technique, original image is subjected to third level lifting wavelet transform (LWT) followed by singular value decomposition (SVD). Watermark is split into two parts to embed each of them into a different subband. In the suggested scheme, firefly algorithm is employed to get optimum solutions for two scaling factors to balance trade-off amid invisibility and robustness. Security in digitized data is an important aspect of image processing. It is improved with a key, an input to Arnold transform for scrambling watermark, to watermark embedding and extraction procedures. All the performance parameters like peak signal to noise ratio (PSNR), structural similarity index measure (SSIM), normalized correlation coefficient (NCC) and bit error rate (BER) are used in formulating maximization objective function. Evaluation of the proposed algorithm indicates that it is characterized by fairly good robustness, invisibility and security.

Keywords:
Digital watermarking Robustness (evolution) Watermark Scrambling Peak signal-to-noise ratio Algorithm Computer science Embedding Singular value decomposition Wavelet transform Maximization Artificial intelligence Mathematics Wavelet Computer vision Mathematical optimization Image (mathematics)

Metrics

2
Cited By
0.25
FWCI (Field Weighted Citation Impact)
36
Refs
0.48
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Steganography and Watermarking Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Brain Tumor Detection and Classification
Life Sciences →  Neuroscience →  Neurology
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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