Embedding capacity, image quality and embedding security are three of the most important performance indicators for image-based reversible data hiding. Over the past few years, extensive studies have been carried out in improving embedding capacity and image quality. However, little progress is made in enhancing embedding security, which represents the robustness to detection from modern steganalyzers....

Concept map (CM) has been proved to be pretty efficient in learning assessment. Existing CM-based learning assessment methods tend to compare a CM delivered by a student against a standard version or expert version. This manuscript employs CM as a technique to assess students’ learning performance from the results of a bunch of traditional performance assessments. The experimental results show a more ...

Along with the popularization of high-speed internet and high-performance digital cameras, the consumption prosperity of high-resolution videos and pictures appears. However, high-performance cameras bring about content infringes through illegal videotaping, which greatly damages the privileges and benefits of the content owners. Multimedia forensics is one of the most important copyright protection ...

In order to improve the accuracy of short-term PM2.5 prediction, we proposed a new hybrid solution that combines several machine learning techniques. Firstly, a set of phase space features are obtained from PM2.5 historical data based on PSR technique and combined with numerical weather prediction (NWP) data to construct a pool of candidate features. Secondly, the optimal feature subset is selected ...

Pixel clustering is a technique of content-adaptive data embedding in the area of high-performance reversible data hiding (RDH). Using pixel clustering, the pixels in a cover image can be classified into different groups based on a single factor, which is usually the local complexity. Since finer pixel clustering seems to improve the embedding performance, in this manuscript, we propose using two factors ...

In the area of reversible data hiding (RDH), multiple-histograms modification (MHM) has been widely recognized as one of the most high-performance techniques. With MHM, the correlation between the prediction-error (PE) and the local complexity (LC) can be well exploited for pixel sorting based data embedding, which is very important in MHM-based RDH algorithms for the obtained high image quality and ...

Most reversible data hiding (RDH) algorithms for color images directly embed secret information in the luminance channel. As a result, the grayscale version of the color image is usually distorted. Since many color image processing algorithms work on the grayscale version, their performance on marked color images may get seriously impacted. Therefore, RD H with grayscale invariance (RDH-GI) is advanced ...

Domain adaptation for classification is often encountered in recent years. A popular approach consists in transforming the source and target data to an identical linear space. Then the Maximum Mean Discrepancy (MMD) is used to evaluate the dissimilarity of distributions. However, the MMD only makes the source and target domain distribution consistent according to the global probability distribution,...

In the area of reversible data hiding (RDH), one of the most popular techniques is prediction-error expansion (PEE), which hides data in the prediction errors with well-preserved image fidelity. The key to a successful PEE-based RDH implementation usually lies in prediction algorithms with high accuracy. Existing PEE-based RDH works often employ one single prediction algorithm, which is usually globally ...

With the rapid development of computer technology, the efficient dissemination of digital images has accelerated information sharing while also intensifying the risk of copyright infringement. Traditional digital watermarking technologies struggle to meet copyright protection requirements in complex scenarios due to insufficient robustness and significant visual interference. This research proposes ...