RST invariant watermarking technique for vector map based on LCA-transform

Abstract

The dangers of copyright protection can impact 2D vector maps, having a knock-on effect on the use of vector data. To achieve invariance property, uniform RST (rotation, scaling and translation) and disguising the digital vector map's information by implementing distortion control, is all done by using watermarking schemes. Convert an original map, then engrain the watermark. An LCA algorithm is used in this study, as a newly proposed way to protect the vector maps under copyright. The procedure is operated in this order: 1) use an original map, altered by the LCA algorithm, 2) use the coefficient of the transformation to engrain the watermark, inserting the resulting frequency into the LSB wave, 3) the watermarked map is acquired by using the inverse LCA map transformation. Further investigations discovered that the necessary standards of fidelity and invisibility can be achieved using this technique. This procedure also gives out numerous frequency domains for digital watermarking; as well as being resilient to signal and geometric invasions.

Secure fragile watermarking based on Huffman encoding and optimal embedding strategy

“…Spectral domain-based watermarking approaches are known for their good robustness against multiple attacks [9], [10]. Many research works have been carried out, Al-ardhi et al [11] used a watermarking scheme based on linear cellular automata transform (LCAT) algorithm operating in the spectral domain to protect the vector maps under copyright, the proposed scheme presents robustness against geometric attacks, namely, translation, scaling, and rotation. To reach the same goal, Neyman et al [12] proposed a watermarking algorithm based on the fast fourier transform (FFT) to embed a copyright marker into vector map.…”

Blind Digital Watermarking Algorithm against Projection Transformation for Vector Geographic Data

“…Many research efforts have been devoted to improving the robustness of watermarking algorithms [11][12][13][14]. These efforts have led watermarking algorithms less vulnerable to compression, filtering, point addition and deletion [15][16][17][18][19][20]. However, as a common processing method of vector geographic data, projection transformation will cause the coordinate values and geometric shapes of vector geographic data to change [21].…”