scholarly journals Radial Level Planarity with Fixed Embedding

2021 ◽  
Vol 25 (1) ◽  
pp. 353-366
Author(s):  
Guido Brückner ◽  
Ignaz Rutter
Keyword(s):  
Level Planarity ◽  
Fixed Embedding

scholarly journals An Adaptive Embedding Strength Watermarking Algorithm Based on Shearlets’ Capture Directional Features

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1377
Author(s):  
Qiumei Zheng ◽  
Nan Liu ◽  
Fenghua Wang
Keyword(s):  
Artificial Bee Colony ◽  
Discrete Wavelet ◽  
Geometric Attacks ◽  
Bee Colony ◽  
Adaptive Embedding ◽  
Strong Robustness ◽  
Simulation Results ◽  
Fixed Embedding ◽  
False Positive Problem ◽  
Made In

The discrete wavelet transform (DWT) is unable to represent the directional features of an image. Similarly, a fixed embedding strength is not able to establish an ideal balance between imperceptibility and robustness of a watermarked image. In this work, we propose an adaptive embedding strength watermarking algorithm based on shearlets’ capture directional features (S-AES). We improve the watermarking algorithm in the domain of DWT using non-subsampled shearlet transform (NSST). The improvement is made in terms of coping with anti-geometric attacks. The embedding strength is optimized by artificial bee colony (ABC) to achieve higher robustness under the premise of satisfying imperceptibility. The principle components (PC) of the watermark are embedded into the host image to overcome the false positive problem. The simulation results show that the proposed algorithm has better imperceptibility and strong robustness against multi-attacks, especially those of high intensity.

scholarly journals THE POINT-SET EMBEDDABILITY PROBLEM FOR PLANE GRAPHS

2013 ◽  
Vol 23 (04n05) ◽  
pp. 357-395 ◽  
Author(s):  
THERESE BIEDL ◽  
MARTIN VATSHELLE
Keyword(s):  
Planar Graph ◽  
Planar Graphs ◽  
Line Drawing ◽  
Np Hard ◽  
Bounded Treewidth ◽  
Straight Line ◽  
Triangulated Graphs ◽  
Point Set ◽  
Fixed Embedding ◽  
Set Of Points

In this paper, we study the point-set embeddability problem, i.e., given a planar graph and a set of points, is there a mapping of the vertices to the points such that the resulting straight-line drawing is planar? It was known that this problem is NP-hard if the embedding can be chosen, but becomes polynomial for triangulated graphs of treewidth 3. We show here that in fact it can be answered for all planar graphs with a fixed combinatorial embedding that have constant treewidth and constant face-degree. We prove that as soon as one of the conditions is dropped (i.e., either the treewidth is unbounded or some faces have large degrees), point-set embeddability with a fixed embedding becomes NP-hard. The NP-hardness holds even for a 3-connected planar graph with constant treewidth, triangulated planar graphs, or 2-connected outer-planar graphs. These results also show that the convex point-set embeddability problem (where faces must be convex) is NP-hard, but we prove that it becomes polynomial if the graph has bounded treewidth and bounded maximum degree.

An Adjustable Interpolation-based Data Hiding Algorithm Based on LSB Substitution and Histogram Shifting

2016 ◽  
Vol 8 (2) ◽  
pp. 48-61 ◽  
Author(s):  
Yuan-Yu Tsai ◽  
Yao-Hsien Huang ◽  
Ruo-Jhu Lin ◽  
Chi-Shiang Chan
Keyword(s):  
Image Processing ◽  
Data Hiding ◽  
Adjustment Process ◽  
Histogram Shifting ◽  
Embedding Capacity ◽  
Visual Distortion ◽  
Capacity Calculation ◽  
Block Complexity ◽  
Fixed Embedding ◽  
Lsb Substitution

Data hiding can be regarded as a type of image processing techniques. Other image processing operations are usually integrated to increase the embedding capacity or decrease the visual distortion. Interpolation is an example of this type of operation. However, previous interpolation-based data hiding algorithms suffered from low and fixed embedding capacity and high visual distortion. This study proposes a more effective two-stage data hiding algorithm based on interpolation, LSB substitution, and histogram shifting. First, the authors modify the formula for embedding capacity calculation and make some adjustments on the sample pixels determination. A threshold is used to obtain the block complexity and each embeddable pixel has a different amount of message embedded. Second, an LSB substitution method and an optimal pixel adjustment process are adopted to raise the image quality. Finally, the authors' proposed algorithm can support adjustable embedding capacity. Compared to the previous algorithm, the experimental results demonstrate the feasibility of the proposed method.

Beyond Level Planarity

2016 ◽  
pp. 482-495 ◽  
Author(s):  
Patrizio Angelini ◽  
Giordano Da Lozzo ◽  
Giuseppe Di Battista ◽  
Fabrizio Frati ◽  
Maurizio Patrignani ◽  
...  
Keyword(s):  
Level Planarity

scholarly journals PVO-Based Reversible Data Hiding Exploiting Two-Layer Embedding for Enhancing Image Fidelity

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1164
Author(s):  
Chin-Feng Lee ◽  
Jau-Ji Shen ◽  
Yi-Jhen Wu ◽  
Somya Agrawal
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Block Size ◽  
Threshold Value ◽  
Difference Expansion ◽  
Secret Data ◽  
Prediction Error Expansion ◽  
Previous State ◽  
Pixel Value ◽  
Fixed Embedding

Recently, Li et al. proposed a data hiding method based on pixel value ordering (PVO) and prediction error expansion (PEE). In their method, maximum and minimum values were predicted and the pixel values were modified to embed secret data. Thereafter, many scholars have proposed improvisations to the original PVO method. In this paper, a Reversible data hiding (RDH) method is proposed where the secret data is dispersed into two layers using different modes of operations. The second layer changes the dividing mode, and the first and the second layers do not take duplicate blocks. Under a fixed embedding capacity, threshold value and block size are controlled, complex blocks are filtered and the secret data is hidden in smooth blocks. This paper also compares the effectiveness of four well-known PVO series methods, the latest PVO methods, difference expansion (DE) method and reduced difference expansion (RDE) method. Experimental results show that the proposed method reduces distortion in the image, thereby enhancing the visual symmetry/quality compared to previous state-of-the-art methods and increasing its high application value.

scholarly journals A New Digital Watermarking Method for Data Integrity Protection in the Perception Layer of IoT

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Guoyin Zhang ◽  
Liang Kou ◽  
Liguo Zhang ◽  
Chao Liu ◽  
Qingan Da ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Low Cost ◽  
Security Analysis ◽  
Data Integrity ◽  
Sensor Nodes ◽  
Security Vulnerabilities ◽  
Protection Scheme ◽  
Integrity Protection ◽  
Fixed Embedding ◽  
Further Development

Since its introduction, IoT (Internet of Things) has enjoyed vigorous support from governments and research institutions around the world, and remarkable achievements have been obtained. The perception layer of IoT plays an important role as a link between the IoT and the real world; the security has become a bottleneck restricting the further development of IoT. The perception layer is a self-organizing network system consisting of various resource-constrained sensor nodes through wireless communication. Accordingly, the costly encryption mechanism cannot be applied to the perception layer. In this paper, a novel lightweight data integrity protection scheme based on fragile watermark is proposed to solve the contradiction between the security and restricted resource of perception layer. To improve the security, we design a position random watermark (PRW) strategy to calculate the embedding position by temporal dynamics of sensing data. The digital watermark is generated by one-way hash function SHA-1 before embedding to the dynamic computed position. In this way, the security vulnerabilities introduced by fixed embedding position can not only be solved effectively, but also achieve zero disturbance to the data. The security analysis and simulation results show that the proposed scheme can effectively ensure the integrity of the data at low cost.

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