Frequency: Quarterly E- ISSN: 2277-6281 P- ISSN: Awaited Abstracted/ Indexed in: CNKI Scholar (China National Knowledge Infrastructure), Ulrichâ??s International Periodical Directory, Google Scholar, SCIRUS, getCITED, Genamics JournalSeek
â??Inventi Rapid/Impact: Multimediaâ?? is a scholarly peer-reviewed international journal published quarterly. It invites original, unpublished or pre-published research and review articles. This journal covers multiple media types, used harmoniously together in creating new experiences including image, video, audio and text.
A novel watermarking framework for scalable coded video that improves the robustness against quality scalable compression is\r\npresented in this paper. Unlike the conventional spatial-domain (t + 2D) water-marking scheme where the motion compensated\r\ntemporal filtering (MCTF) is performed on the spatial frame-wise video data to decompose the video, the proposed framework\r\napplies the MCTF in the wavelet domain (2D + t) to generate the coefficients to embed the watermark. Robustness performances\r\nagainst scalable content adaptation, such asMotion JPEG 2000, MC-EZBC, or H.264-SVC, are reviewed for various combinations\r\nof motion compensated 2D+t+2D using the proposed framework. The MCTF is improved by modifying the update step to\r\nfollow the motion trajectory in the hierarchical temporal decomposition by using direct motion vector fields in the update step and\r\nimplied motion vectors in the prediction step. The results show smaller embedding distortion in terms of both peak signal to noise\r\nratio and flickering metrics compared to frame-by-frame video watermarking while the robustness against scalable compression is\r\nimproved by using 2D + t over the conventional t + 2D domain video watermarking, particularly for blind watermarking schemes\r\nwhere the motion is estimated from the watermarked video....
While the reconstruction of 3D objects is increasingly used today, the simplification of 3D point cloud, however, becomes a\nsubstantial phase in this process of reconstruction. This is due to the huge amounts of dense 3D point cloud produced by 3D\nscanning devices. In this paper, a new approach is proposed to simplify 3D point cloud based on k-nearest neighbor (k-NN) and\nclustering algorithm. Initially, 3D point cloud is divided into clusters using k-means algorithm. Then, an entropy estimation is\nperformed for each cluster to remove the ones that have minimal entropy. In this paper, MATLAB is used to carry out the\nsimulation, and the performance of our method is testified by test dataset. Numerous experiments demonstrate the effectiveness of\nthe proposed simplification method of 3D point cloud....
This paper proposes a method of encrypting images with password protection for secure sharing based on deoxyribonucleic acid\n(DNA) sequence operations and the tangent-delay ellipse reflecting the cavity-map system (TD-ERCS). The initial values of the\nTD-ERCS system are generated from a userâ??s password, and the TD-ERCS system is used to scramble the pixel locations of the R,\nG, and B matrices of the original image. Next, three DNA-sequence matrices are generated by encoding the permuted color image\nsuch that it can be transformed into three matrices. Then, the TD-ERCS system is employed to generate three chaotic sequences\nbefore encoding the DNA into the three matrices. Thereafter, a DNA exclusive OR (XOR) operation is executed between the DNA\nsequences of the permuted image and the DNA sequences generated by the TD-ERCS system to produce three encrypted\nscrambled matrices. Finally, the matrices of the DNA sequences are decoded, and the R, G, and B channels are recombined to form\nan encrypted color image. The results of simulation and security tests reveal that the proposed algorithm offers robust encryption\nand demonstrates the ability to resist exhaustive, statistical, and differential attacks....
In order to generate color test image consistent with human perception in aspect of saturation, lightness, and hue of image, we\r\npropose a saturation test image design method based on CIEDE2000 color difference formula. This method exploits the subjective\r\nsaturation parameter C of CIEDE2000 to get a series of test images with different saturation but same lightness and hue. It is\r\nfound experimentally that the vision perception has linear relationship with the saturation parameter C. This kind of saturation\r\ntest image has various applications, such as in the checking of color masking effect in visual experiments and the testing of the\r\nvisual effects of image similarity component....
This study adopts a triangle subdivision scheme to achieve reversible data embedding. The secret message is embedded into the\nnewly added vertices. The topology of added vertex is constructed by connecting it with the vertices of located triangle. For\nfurther raising the total embedding capacity, a recursive subdivision mechanism, terminated by a given criterion, is employed.\nFinally, a principal component analysis can make the stego model against similarity transformation and vertex/triangle reordering\nattacks. Our proposed algorithm can provide a high and adjustable embedding capacity with reversibility.The experimental results\ndemonstrate the feasibility of our proposed algorithm....
Omnidirectional, or 360Degree, cameras are able to capture the surrounding space, thus providing\nan immersive experience when the acquired data is viewed using head mounted displays.\nSuch an immersive experience inherently generates an illusion of being in a virtual environment.\nThe popularity of 360Degree media has been growing in recent years. However, due to the large amount\nof data, processing and transmission pose several challenges. To this aim, efforts are being devoted\nto the identification of regions that can be used for compressing 360Degree images while guaranteeing\nthe immersive feeling. In this contribution, we present a saliency estimation model that considers\nthe spherical properties of the images. The proposed approach first divides the 360Degree image into multiple\npatches that replicate the positions (viewports) looked at by a subject while viewing a 360Degree image\nusing a head mounted display. Next, a set of low-level features able to depict various properties of\nan image scene is extracted from each patch. The extracted features are combined to estimate the 360Degree\nsaliency map. Finally, bias induced during image exploration and illumination variation is fine-tuned\nfor estimating the final saliency map. The proposed method is evaluated using a benchmark 360Degree image\ndataset and is compared with two baselines and eight state-of-the-art approaches for saliency estimation.\nThe obtained results show that the proposed model outperforms existing saliency estimation models....
As a greater number ofWeb Services are made available today, automatic discovery is recognized as an important task. To promote\r\nthe automation of service discovery, different semantic languages have been created that allow describing the functionality of\r\nservices in a machine interpretable form using Semantic Web technologies. The problem is that users do not have intimate\r\nknowledge about semantic Web service languages and related toolkits. In this paper, we propose a discovery framework that\r\nenables semanticWeb service discovery based on keywords written in natural language.We describe a novel approach for automatic\r\ndiscovery of semantic Web services which employs Natural Language Processing techniques to match a user request, expressed in\r\nnatural language, with a semantic Web service description. Additionally, we present an efficient semantic matching technique to\r\ncompute the semantic distance between ontological concepts....
With the technological advances in the areas of Machine-To-Machine (M2M) and\nDevice-To-Device (D2D) communication, various smart computing devices now integrate a set\nof multimedia sensors such as accelerometers, barometers, cameras, fingerprint sensors, gestures,\niris scanners, etc., to infer the environmental status. These devices are generally identified using\nradio-frequency identification (RFID) to transfer the collected data to other local or remote objects over\na geographical location. To enable automatic data collection and transition, a valid RFID embedded\nobject is highly recommended. It is used to authorize the devices at various communication phases.\nIn smart application devices, RFID-based authentication is enabled to provide short-range operation.\nOn the other hand, it does not require the communication device to be in line-of-sight to gain server\naccess like bar-code systems. However, in existing authentication schemes, an adversary may capture\nprivate user data to create a forgery problem. Also, another issue is the high computation cost. Thus,\nseveral studies have addressed the usage of context-aware authentication schemes for multimedia\ndevice management systems. The security objective is to determine the user authenticity in order to\nwithhold the eavesdropping and tracing. Lately, RFID has played a significant for the context-aware\nsensor management systems (CASMS) as it can reduce the complexity of the sensor systems, it can be\navailable in access control, sensor monitoring, real time inventory and security-aware management\nsystems. Lately, this technology has opened up its wings for CASMS, where the challenging issues\nare tag-anonymity, mutual authentication and untraceability. Thus, this paper proposes a secure\nhash-based RFID mechanism for CASMS. This proposed protocol is based on the hash operation with\nthe synchronized secret session-key to withstand any attacks, such as desynchronization, replay and\nman-in-the-middle. Importantly, the security and performance analysis proves that the proposed\nhash-based protocol achieves better security and performance efficiencies than other related schemes.\nFrom the simulation results, it is observed that the proposed scheme is secure, robust and less\nexpensive while achieving better communication metrics such as packet delivery ratio, end-to-end\ndelay and throughput rate....
The Internet of vehicles (IoV) is a newly emerged wave that converges Internet of things (IoT) into vehicular networks to benefit\nfrom ubiquitous Internet connectivity. Despite various research efforts, vehicular networks are still striving to achieve higher data\nrate, seamless connectivity, scalability, security, and improved quality of service, which are the key enablers for IoV. It becomes\neven more critical to investigate novel design architectures to accomplish efficient and reliable data forwarding when it comes to\nhandling the emergency communication infrastructure in the presence of natural epidemics. The article proposes a heterogeneous\nnetwork architecture incorporating multiple wireless interfaces (e.g., wireless access in vehicular environment (WAVE), longrange\nwireless fidelity (WiFi), and fourth generation/long-term evolution (4G/LTE)) installed on the on-board units, exploiting\nthe radio over fiber approach to establish a context-aware network connectivity. This heterogeneous network architecture attempts\nto meet the requirements of pervasive connectivity for vehicular ad hoc networks (VANETs) to make them scalable and\nadaptable for IoV supporting a range of emergency services. The architecture employs the Best Interface Selection (BIS) algorithm\nto always ensure reliable communication through the best available wireless interface to support seamless connectivity required\nfor efficient data forwarding in vehicle to infrastructure (V2I) communication successfully avoiding the single point of failure.\nMoreover, the simulation results clearly argue about the suitability of the proposed architecture in IoV environment coping with\ndifferent types of applications against individual wireless technologies....
Online Social Networks (OSNs) have found widespread applications in every area of our\nlife. A large number of people have signed up to OSN for different purposes, including to meet\nold friends, to choose a given company, to identify expert users about a given topic, producing\na large number of social connections. These aspects have led to the birth of a new generation\nof OSNs, called Multimedia Social Networks (MSNs), in which user-generated content plays a key\nrole to enable interactions among users. In this work, we propose a novel expert-finding technique\nexploiting a hypergraph-based data model for MSNs. In particular, some user-ranking measures,\nobtained considering only particular useful hyperpaths, have been profitably used to evaluate the\nrelated expertness degree with respect to a given social topic. Several experiments on Last.FM have\nbeen performed to evaluate the proposed approachâ??s effectiveness, encouraging future work in this\ndirection for supporting several applications such as multimedia recommendation, influence analysis,\nand so on....
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