Reversible data hiding in low complexity and high quality compression scheme
Section snippets
Jing-Ming Guo (Mʼ06–SMʼ10) was born in Kaohsiung, Taiwan, in 1972. He received the B.S.E.E. and M.S.E.E. degrees from National Central University, Taoyuan, Taiwan, in 1995 and 1997, respectively, and the Ph.D. degree from the Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan, in 2004. From 1998 to 1999, he was an Information Technique Officer with the Chinese Army. From 2003 to 2004, he was granted the National Science Council scholarship for advanced research
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Cited by (17)
Reversible data hiding in halftone images based on minimizing the visual distortion of pixels flipping
2020, Signal ProcessingCitation Excerpt :Since halftone images are still used as storage and transportation carriers, it is still worth studying on the halftone image RDH for the existence and usage of halftone images, although RDH for halftone images has received less attention in recent years. Some RDH methods [11–17] in gray-scale, color images or encrypted images have been released. There are some RDH methods based on difference expansion (DE) proposed in [18–20].
Reversible data hiding in binary images by flipping pattern pair with opposite center pixel
2020, Journal of Visual Communication and Image RepresentationCitation Excerpt :In some cases, the distortion is intolerable and it is necessary to recover the original images. Consequently, reversible data hiding (RDH) is proposed as a technique to recover the hidden messages and the original images completely [12–15]. So far, a considerable number of RDH methods have been proposed focusing on gray-scale or color images [16–18].
Securing visual search queries in ubiquitous scenarios empowered by smart personal devices
2020, Information SciencesCitation Excerpt :This aspect opens interesting perspectives that could be exploited in several different ways. Future works will include the improvement of the proposed approach, by designing ad-hoc and more efficient watermarking techniques or ad-hoc reversible data hiding techniques (e.g., based on [12] or other similar approaches). In addition, we intend to further consider all the aspects related to the privacy preservation, which are important and essential in the search and mobile search contexts, as highlighted in [22–24].
Dither matrix estimation based on pixel histograms of halftones
2018, Signal ProcessingCitation Excerpt :Even in some of the methods not based on dithering models, the thresholds are still demanded to generate the halftones for training the inverse algorithms [4,10–14]. In addition to the inverse halftoning, some examples can also be found in data hiding or watermarking [15,16], where the decoder needs the thresholds to extract the embedded data. In most of the applications such as the examples just mentioned, the thresholds were assumed known for convenience.
New data-hiding algorithm based on adaptive neural networks with modified particle swarm optimization
2015, Computers and SecurityA recent survey of reversible watermarking techniques
2014, Information SciencesCitation Excerpt :Zheng et al. reported a comprehensive survey on robust image watermarking alogorithms [114]. Guo [35] and Guo et al. [36] reported reversible watermarking techniques for the halftone images. In past, reviews of different reversible watermarking techniques were also carried out [8,28,83].
Jing-Ming Guo (Mʼ06–SMʼ10) was born in Kaohsiung, Taiwan, in 1972. He received the B.S.E.E. and M.S.E.E. degrees from National Central University, Taoyuan, Taiwan, in 1995 and 1997, respectively, and the Ph.D. degree from the Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan, in 2004. From 1998 to 1999, he was an Information Technique Officer with the Chinese Army. From 2003 to 2004, he was granted the National Science Council scholarship for advanced research from the Department of Electrical and Computer Engineering, University of California, Santa Barbara. He is currently a Professor with the Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei. His research interests include multimedia signal processing, multimedia security, computer vision, and digital halftoning.
Dr. Guo is a senior member of the IEEE Signal Processing Society. He received the Outstanding Youth Electrical Engineer Award from Chinese Institute of Electrical Engineering in 2011, the Outstanding Young Investigator Award from the Institute of System Engineering in 2011, the Best Paper Award from the IEEE International Conference on System Science and Engineering in 2011, the Excellence Teaching Award in 2009, the Research Excellence Award in 2008, the Acer Dragon Thesis Award in 2005, the Outstanding Paper Awards from IPPR, Computer Vision and Graphic Image Processing in 2005 and 2006, and the Outstanding Faculty Award in 2002 and 2003.