Image Watermarking based on Huffman Coding and Laplace Sharpening - Muna M. Lafta (College of Education for Women, 2019)
In this paper, an algorithm through which we can embed more data than the regular methods under spatial domain is introduced. We compressed the secret data using Huffman coding and then this compressed data is embedded using laplacian sharpening method. We used Laplace filters to determine the effective hiding places, then based on threshold value we found the places with the highest values acquired from these filters for embedding the watermark. In this work our aim is increasing the capacity of information which is to be embedded by using Huffman code and at the same time increasing the security of the algorithm by hiding data in the places that have highest values of edges and less noticeable. The performance of the proposed algorithm is evaluated using detection techniques such as Peak Signal- to- Noise Ratio (PSNR) to measure the distortion, Similarity Correlation between the cover-image and watermarked image, and Bit Error Rate (BER) is used to measure the robustness. The sensitivity against attacks on the watermarked image is investigated. The types of attacks applied are: Laplacian sharpening, Median filtering, Salt & Peppers Noise and Rotating attack. The results show that the proposed algorithm can resist Laplacain sharpening with any sharpening parameter k, besides laplacian good result according to some other types of attacks is achieved.