In this paper, a robust invisible watermarking system for digital video encoded by MPEG-4 is presented. The proposed scheme provides watermark hidden by embedding a secret message (watermark) in the sprite area allocated in reference frame (I-frame). The proposed system consists of two main units: (i) Embedding unit and (ii) Extraction unit. In the embedding unit, the system allocates the sprite blocks using motion compensation information. The allocated sprite area in each I–frame is used as hosting area for embedding watermark data. In the extraction unit, the system extracts the watermark data in order to check authentication and ownership of the video. The watermark data embedding method is Blocks average modulation applied on RGB dom

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Since the Internet has been more widely used and more people have access to multimedia content, copyright hacking, and piracy have risen. By the use of watermarking techniques, security, asset protection, and authentication have all been made possible. In this paper, a comparison between fragile and robust watermarking techniques has been presented to benefit them in recent studies to increase the level of security of critical media. A new technique has been suggested when adding an embedded value (129) to each pixel of the cover image and representing it as a key to thwart the attacker, increase security, rise imperceptibility, and make the system faster in detecting the tamper from unauthorized users. Using the two watermarking ty

  With the fast progress of information technology and the computer networks, it becomes very easy to reproduce and share the geospatial data due to its digital styles. Therefore, the usage of geospatial data suffers from various problems such as data authentication, ownership proffering, and illegal copying ,etc. These problems can represent the big challenge to future uses of the geospatial data. This paper introduces a new watermarking scheme to ensure the copyright protection of the digital vector map. The main idea of proposed scheme is based on transforming  the digital map to frequently domain using the Singular Value Decomposition (SVD) in order to determine suitable areas to insert the watermark data.

The progress of network and multimedia technologies has been phenomenal during the previous two decades. Unauthorized users will be able to copy, retransmit, modify reproduction, and upload the contents more easily as a result of this innovation. Malicious attackers are quite concerned about the development and widespread use of digital video. Digital watermarking technology gives solutions to the aforementioned problems. Watermarking methods can alleviate these issues by embedding a secret watermark in the original host data, allowing the genuine user or file owner to identify any manipulation. In this study, lots of papers have been analyzed and studied carefully, in the period 2011–2022. The historical basis of the subject shou

In this research paper, a new blind and robust fingerprint image watermarking scheme based on a combination of dual-tree complex wavelet transform (DTCWT) and discrete cosine transform (DCT) domains is demonstrated. The major concern is to afford a solution in reducing the consequence of geometric attacks. It is due to the fingerprint features that may be impacted by the incorporated watermark, fingerprint rotations, and displacements that result in multiple feature sets. To integrate the bits of the watermark sequence into a differential process, two DCT-transformed sub-vectors are implemented. The initial sub-vectors were obtained by sub-sampling in the host fingerprint image of both real and imaginary parts of the DTCWT wavelet coeffi

Iresineherbstii (blood leaves) is a member of the Amaranthaceae family, native to tropical and subtropical areas. It is erect herbaceous, has red and white variety. Different phytochemical constituents were detected as alkaloids, flavonoids, anthocyanins, and others. This herb was used as a pH indicator, insecticide, and dye fabrics. Traditionally it was used for divination purposes and other purposes. Iresinin IV is the major colorant. Different studies were done to evaluate the CNS, immunomodulatory, antibacterial, antiviral, cytotoxic and other effects. Fresh leaves extract was hepatotoxic. This review aimed to demonstrate the morphological features of this herb and to show the clinical studies related to its traditional use.

 The use of multimedia technology is growing every day, and it is difficult and time-consuming to provide allowed data while preventing secret information from being used without authorization. The material that has been watermarked can only be accessed by authorized users. Digital watermarking is a popular method for protecting digital data. The embedding of secret data into actual information is the subject of digital watermarking. This paper examines watermarking techniques, methodologies, and attacks, as well as the development of watermarking digital images stored in both the spatial and frequency domains.

Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. In addition, reliable sensing creates spectrum opportunities for capacity increase of cognitive networks. One of the key challenges in spectrum sensing is the robust detection of primary signals in highly negative signal-to-noise regimes (SNR).In this paper ,