caa a22 4500 606199225 CHVBK 20210128100937.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s11045-013-0257-0 doi (NATIONALLICENCE)springer-10.1007/s11045-013-0257-0 A geometrical attack resistant image watermarking algorithm based on histogram modification [Elektronische Daten] [Xuansen He, Tao Zhu, Gaobo Yang] In order to avoid geometric distortions in watermark embedding, a geometrical attack resistant image watermarking algorithm is proposed based on histogram modification. The watermark information is embedded into the host image by modifying the number of the gray samples of the image histogram. In a fixed gray range, every three consecutive bins are divided into a group for embedding one-bit watermark, through modifying the sample value of a bin to another of the adjacent bin to realize the watermark insertion. Moreover, to avoid duplicate modification and improve the transparency, only one bin is modified every two neighbor bins, the modified histogram is mapped into the watermarked image. For watermark detection, it is in fact an inverse process of watermark embedding. Watermark is extracted through calculating and judging the relationship of the number of samples of the three successive bins. The experimental results show that the algorithm is robust to both geometrical attacks and those conventional signal processing attacks. Springer Science+Business Media New York, 2013 Image watermarking nationallicence Histogram modification nationallicence Geometrical attacks nationallicence Conventional signal processing attacks nationallicence Combination attacks nationallicence He Xuansen Changsha, Hunan, China aut Zhu Tao Changsha, Hunan, China aut Yang Gaobo Changsha, Hunan, China aut Multidimensional Systems and Signal Processing Springer US; http://www.springer-ny.com 26/1(2015-01-01), 291-306 0923-6082 26:1<291 2015 26 11045 https://doi.org/10.1007/s11045-013-0257-0 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11045-013-0257-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- He Xuansen Changsha, Hunan, China aut NATIONALLICENCE 700 1- Zhu Tao Changsha, Hunan, China aut NATIONALLICENCE 700 1- Yang Gaobo Changsha, Hunan, China aut NATIONALLICENCE 773 0- Multidimensional Systems and Signal Processing Springer US; http://www.springer-ny.com 26/1(2015-01-01), 291-306 0923-6082 26:1<291 2015 26 11045