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Nan-I Wu

Researcher at Toko University

Publications -  8
Citations -  924

Nan-I Wu is an academic researcher from Toko University. The author has contributed to research in topics: Steganography & Pixel. The author has an hindex of 7, co-authored 8 publications receiving 862 citations. Previous affiliations of Nan-I Wu include National Chung Hsing University.

Papers
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(Journal of Systems and Software, 81(1):150-158)A high quality steganographic method with pixel-value differencing and modulus function

TL;DR: A new image steganographic technique capable of producing a secret-embedded image that is totally indistinguishable from the original image by the human eye is proposed, and the proposed scheme is secure against the RS detection attack.
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A high quality steganographic method with pixel-value differencing and modulus function

TL;DR: Wang et al. as mentioned in this paper proposed an image steganographic technique capable of producing a secret-embedded image that is totally indistinguishable from the original image by the human eye, which avoids the falling-off-boundary problem by using pixel-value differencing and the modulus function.
Journal Article

Data Hiding: Current Status and Key Issues

TL;DR: This survey paper is focused on the development and current status of steganographic techniques for grayscale images, and shall separately introduce schemes with high hiding capacities and scheme with high imperceptibility.
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A novel adaptive steganography based on local complexity and human vision sensitivity

TL;DR: A novel adaptive steganographic scheme that is capable of both preventing visual degradation and providing a large embedding capacity superior to that offered by a number of existing schemes is presented.
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Exploring pixel-value differencing and base decomposition for low distortion data embedding

TL;DR: This paper presents a low distortion data embedding method using pixel-value differencing and base decomposition schemes, which is capable of embedding large amounts of a message, yet still produces the embedded image with very low distortion.