Watermarking Using Energy-LSB Embedded Method

Watermarking Using Energy-LSB Embedded Method


  • sajad altimime Informatics Institute for Postgraduate Studies
  • Dr. zainab mohammad hussain




watermark, Energy, (Least Significant Bits) LSB, MSE,SNR, PSNR.


Digital watermarking technology is increasingly used to protect copyright and demonstrate ownership of digital multimedia (such as text, music, photos, and videos). In order to safeguard intellectual property rights and rules of ownership for multimedia, this project suggests a text watermark algorithm. The process of hiding little text or grayscale images is the main focus, though. The masking of a watermark text in a high-color or high-density area of the block picture has been proposed using an embedding technique based on an energy function and the Least Significant Bits (LSB) method. Even with various format types and picture sizes chosen to conceal and cover a changing message size, the quality results demonstrate that the watermark image suffers from less distortion than the cover image, and the suggested algorithm is powerful to conceal a random watermark text even with smaller block sizes. An additional optional choice to encrypt the text watermark before embedding is also recommended because doing so would make it harder for hackers to read the text. This text can be encrypted using the Caesar cipher method before embedding is implemented in images.The experimental results of using the suggested algorithm for embedding and extracting watermark text for various sizes in a large number of images were satisfactory, giving a level of peak signal-to-noise ratio (PSNR) and Signal to Noise Ratio (SNR) with low mean square error (MSE) values. However, PSNR degrades more quickly than LBS as the watermark text size increases, so it was determined that it is more suitable for applying a watermark rather than a stego It is employed in order to share information securely


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How to Cite

altimime, sajad, & hussain, zainab. (2022). Watermarking Using Energy-LSB Embedded Method. Wasit Journal of Computer and Mathematics Sciences, 1(3), 140–148. https://doi.org/10.31185/wjcm.53