scholarly journals A Vertex-Based 3D Authentication Algorithm Based on Spatial Subdivision

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 422 ◽  
Author(s):  
Yuan-Yu Tsai ◽  
Yu-Shiou Tsai ◽  
I-Ting Chi ◽  
Chi-Shiang Chan
Keyword(s):  
Experimental Results ◽  
Embedding Capacity ◽  
Space Partitioning ◽  
Authentication Code ◽  
Bounding Volume ◽  
Spatial Subdivision ◽  
Binary Space Partitioning ◽  
Input Model ◽  
High Embedding Capacity

The study proposed a vertex-based authentication algorithm based on spatial subdivision. A binary space partitioning tree was employed to subdivide the bounding volume of the input model into voxels. Each vertex could then be encoded into a series of binary digits, denoted as its authentication code, by traversing the constructed tree. Finally, the above authentication code was embedded into the corresponding reference vertex by modulating its position within the located subspace. Extensive experimental results demonstrated that the proposed algorithm provided high embedding capacity and high robustness. Furthermore, the proposed algorithm supported controllable distortion and self-recovery.

scholarly journals Efficient Reversible Data Hiding Scheme for AMBTC-Compressed Images

2021 ◽  
Vol 11 (15) ◽  
pp. 6741
Author(s):  
Chia-Chen Lin ◽  
Thai-Son Nguyen ◽  
Chin-Chen Chang ◽  
Wen-Chi Chang
Keyword(s):  
Data Hiding ◽  
Free Space ◽  
Reversible Data Hiding ◽  
Secret Message ◽  
Embedding Capacity ◽  
Absolute Moment ◽  
Compressed Images ◽  
High Embedding Capacity ◽  
Significant Attention ◽  
Efficiency Rate

Reversible data hiding has attracted significant attention from researchers because it can extract an embedded secret message correctly and recover a cover image without distortion. In this paper, a novel, efficient reversible data hiding scheme is proposed for absolute moment block truncation code (AMBTC) compressed images. The proposed scheme is based on the high correlation of neighboring values in two mean tables of AMBTC-compressed images to further losslessly encode these values and create free space for containing a secret message. Experimental results demonstrated that the proposed scheme obtained a high embedding capacity and guaranteed the same PSNRs as the traditional AMBTC algorithm. In addition, the proposed scheme achieved a higher embedding capacity and higher efficiency rate than those of some previous schemes while maintaining an acceptable bit rate.

Hardware-Accelerated Dual-Split Trees

2020 ◽  
Vol 3 (2) ◽  
pp. 1-21
Author(s):  
Daqi Lin ◽  
Elena Vasiou ◽  
Cem Yuksel ◽  
Daniel Kopta ◽  
Erik Brunvand
Keyword(s):  
Ray Tracing ◽  
Hardware Acceleration ◽  
Memory Storage ◽  
Compact Representation ◽  
Space Partitioning ◽  
Data Movement ◽  
Bounding Volume ◽  
Bounding Boxes ◽  
Split Trees ◽  
Bounding Volume Hierarchies

Bounding volume hierarchies (BVH) are the most widely used acceleration structures for ray tracing due to their high construction and traversal performance. However, the bounding planes shared between parent and children bounding boxes is an inherent storage redundancy that limits further improvement in performance due to the memory cost of reading these redundant planes. Dual-split trees can create identical space partitioning as BVHs, but in a compact form using less memory by eliminating the redundancies of the BVH structure representation. This reduction in memory storage and data movement translates to faster ray traversal and better energy efficiency. Yet, the performance benefits of dual-split trees are undermined by the processing required to extract the necessary information from their compact representation. This involves bit manipulations and branching instructions which are inefficient in software. We introduce hardware acceleration for dual-split trees and show that the performance advantages over BVHs are emphasized in a hardware ray tracing context that can take advantage of such acceleration. We provide details on how the operations needed for decoding dual-split tree nodes can be implemented in hardware and present experiments in a number of scenes with different sizes using path tracing. In our experiments, we have observed up to 31% reduction in render time and 38% energy saving using dual-split trees as compared to binary BVHs representing identical space partitioning.

scholarly journals High Embedding Capacity Data Hiding Algorithm for H.264/AVC Video Sequences without Intraframe Distortion Drift

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Dinh-Chien Nguyen ◽  
Thai-Son Nguyen ◽  
Chin-Chen Chang ◽  
Huan-Sheng Hsueh ◽  
Fang-Rong Hsu
Keyword(s):  
Digital Media ◽  
Data Hiding ◽  
Video Sequences ◽  
Embedding Capacity ◽  
Secret Data ◽  
Low Distortion ◽  
High Embedding Capacity ◽  
Advanced Video Coding ◽  
Distortion Drift ◽  
Capacity Data

Data hiding is a technique that allows secret data to be delivered securely by embedding the data into cover digital media. In this paper, we propose a new data hiding algorithm for H.264/advanced video coding (AVC) of video sequences with high embedding capacity. In the proposed scheme, to embed secret data into the quantized discrete cosine transform (QDCT) coefficients of I frames without any intraframe distortion drift, some embeddable coefficient pairs are selected in each block, and they are divided into two different groups, i.e., the embedding group and the averting group. The embedding group is used to carry the secret data, and the averting group is used to prevent distortion drift in the adjacent blocks. The experimental results show that the proposed scheme can avoid intraframe distortion drift and guarantee low distortion of video sequences. In addition, the proposed scheme provides enhanced embedding capacity compared to previous schemes. Moreover, the embedded secret data can be extracted completely without the requirement of the original secret data.

scholarly journals Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History

2017 ◽  
Vol 2017 ◽  
pp. 1-22
Author(s):  
Danping Wang ◽  
Kunyuan Hu ◽  
Lianbo Ma ◽  
Maowei He ◽  
Hanning Chen
Keyword(s):  
Particle Swarm Optimization ◽  
Statistical Tests ◽  
Particle Swarm ◽  
Local Optimum ◽  
Space Partitioning ◽  
Swarm Optimization ◽  
Real World Problem ◽  
Binary Space Partitioning ◽  
Solution Accuracy ◽  
Search History

A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH) is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals’ revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional), 10 CEC2005 benchmark functions (30-dimensional), and a real-world problem (multilevel image segmentation problems). Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests.

scholarly journals A novel two-dimensional reversible data hiding method with high embedding capacity in H.264/advanced video coding

2020 ◽  
Vol 16 (3) ◽  
pp. 155014772091100
Author(s):  
Yi Chen ◽  
Hongxia Wang ◽  
Xiaoxu Tang ◽  
Yong Liu ◽  
Hanzhou Wu ◽  
...  
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Error Concealment ◽  
Similarity Index ◽  
Two Dimensional ◽  
Embedding Capacity ◽  
High Embedding Capacity ◽  
Advanced Video Coding

Developing the technology of reversible data hiding based on video compression standard, such as H.264/advanced video coding, has attracted increasing attention from researchers. Because it can be applied in some applications, such as error concealment and privacy protection. This has motivated us to propose a novel two-dimensional reversible data hiding method with high embedding capacity in this article. In this method, all selected quantized discrete cosine transform coefficients are first paired two by two. And then, each zero coefficient-pair can embed 3 information bits and the coefficient-pairs only containing one zero coefficient can embed 1 information bit. In addition, only one coefficient of each one of the rest coefficient-pairs needs to be changed for reversibility. Therefore, the proposed two-dimensional reversible data hiding method can obtain high embedding capacity when compared with the related work. Moreover, the proposed method leads to less degradation in terms of peak-signal-to-noise ratio, structural similarity index, and less impact on bit-rate increase.

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