数字水印
计算机科学
人工智能
算法
模式识别(心理学)
水印
数学
图像(数学)
嵌入
计算机视觉
稳健性(进化)
作者
Ayesha Shaik,V. Masilamani
出处
期刊:2019 IEEE 1st International Conference on Energy, Systems and Information Processing (ICESIP)
日期:2019-07-01
标识
DOI:10.1109/icesip46348.2019.8938355
摘要
This article presents a novel simple linear iterative clustering (SLIC) superpixels and partial pivoting lower triangular upper triangular (PPLU) factorization based zero-watermarking (ZWM) scheme is proposed. The novelty of this article is that the use of SLIC superpixels and PPLU decomposition for ZWM. The original image is subjected to SLIC segmentation and non-overlapping high entropy blocks are selected. On the selected blocks discrete wavelet transform (DWT) is applied and those blocks are undergone PPLU factorization to get three matrices $L, U$ , and $P$ . The product matrix $L\times U$ is used to construct zero-watermark. This work is validated with BOWS, and SIPI datasets, and shown robust against the attacks. The test results demonstrate that this work has better performance than the recent ZWM schemes.
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