Highly Secured Multilayered Motion Vector Watermarking

Acharjee, Suvojit; Chakraborty, Sayan; Samanta, Sourav; Azar, Ahmad Taher; Hassanien, Aboul Ella; Dey, Nilanjan

doi:10.1007/978-3-319-13461-1_13

Cited by 14 publications

(6 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In any case, the proposed method can be combined with the conventional semantic based techniques to achieve a more complete authentication scheme, including those that manipulate syntax elements in audio (e.g., scale factor, MDCT coefficients in MP3 [31]) and video (e.g., prediction mode [32], [33], coefficients [34], motion vectors [35], quantization parameters [36]). For example, the proposed method can be utilized as the first layer of authentication, while the conventional authentication methods for audio [2] and video [4] can be applied to localized modified part of the audio and/or video.…”

Section: Discussionmentioning

confidence: 99%

Lightweight Authentication for MP4 Format Container Using Subtitle Track

Wong

Chan

Maungmaung

2020

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

With massive utilization of video in every aspect of our daily lives, managing videos is crucial and demanding. The rich literature of data embedding has proven its viability in managing as well as enriching videos and other multimedia contents, but conventional methods are designed to operate in the media/compression layer. In this work, the synchronization between the audio-video and subtitle tracks within an MP4 format container is manipulated to insert data. Specifically, the data are derived from the statistics of the audio samples and video frames, and it serves as the authentication data for verification purpose. When needed, the inserted authentication data can be extracted and compared against the information computed from the received audio samples and video frames. The proposed method is lightweight because simple statistics, i.e., '0' and '1' at the bit stream level, are treated as the authentication data. Furthermore, unlike conventional MP4 container format-based data insertion technique, the bit stream size remains unchanged before and after data insertion using the proposed method. The proposed authentication method can also be deployed for joint utilization with any existing authentication technique for audio / video as long as these media can be multiplexed into a single bit stream and contained within an MP4 container. Experiments are carried out to verify the basic functionality of the proposed technique as an authentication method.

show abstract

Section: Discussionmentioning

confidence: 99%

Lightweight Authentication for MP4 Format Container Using Subtitle Track

Wong

Chan

Maungmaung

2020

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

show abstract

“…In motion estimation, motion vectors [176][177][178][179][180] are determined to represent the transformation through adjacent 2D image frames in a video sequence [181]. Motion vectors are computed in two ways [182]-pixel-based methods or direct method, and feature-based methods or indirect method.…”

Section: Motion Estimationmentioning

confidence: 99%

Vision Tracking: A Survey of the State-of-the-Art

et al. 2020

Self Cite

View full text Add to dashboard Cite

Vision tracking is a well-studied framework in vision computing. Developing a robust visual tracking system is challenging because of the sudden change in object motion, cluttered background, partial occlusion and camera motion. In this study, the state-of-the art visual tracking methods are reviewed and different categories are discussed. The overall visual tracking process is divided into four stages-object initialization, appearance modeling, motion estimation, and object localization. Each of these stages is briefly elaborated and related researches are discussed. A rapid growth of visual tracking algorithms is observed in last few decades. A comprehensive review is reported on different performance metrics to evaluate the efficiency of visual tracking algorithms which might help researchers to identify new avenues in this area. Various application areas of the visual tracking are also discussed at the end of the study.

show abstract

“…Rule generation of rough sets theories enables fuzzy threshold values of gray level with specific limit (Roy et al, 2014). Digital watermarking (Hassanien et al, 2014) is another classic example for rough sets application to address the uncertainty during the identifications of the exact features. Apart from that, wireless sensor networks also utilize the rough sets for vehicle communications .…”

Section: Literature Reviewmentioning

confidence: 99%

Theoretical Analysis of Different Classifiers under Reduction Rough Data Set

Ripon

Kamal

Hossain

et al. 2016

International Journal of Rough Sets and Data Analysis

Self Cite

View full text Add to dashboard Cite

Rough set plays vital role to overcome the complexities, vagueness, uncertainty, imprecision, and incomplete data during features analysis. Classification is tested on certain dataset that maintain an exact class and review process where key attributes decide the class positions. To assess efficient and automated learning, algorithms are used over training datasets. Generally, classification is supervised learning whereas clustering is unsupervised. Classifications under mathematical models deal with mining rules and machine learning. The Objective of this work is to establish a strong theoretical and manual analysis among three popular classifier namely K-nearest neighbor (K-NN), Naive Bayes and Apriori algorithm. Hybridization with rough sets among these three classifiers enables enable to address larger datasets. Performances of three classifiers have tested in absence and presence of rough sets. This work is in the phase of implementation for DNA (Deoxyribonucleic Acid) datasets and it will design automated system to assess classifier under machine learning environment.

show abstract

Highly Secured Multilayered Motion Vector Watermarking

Cited by 14 publications

References 22 publications

Lightweight Authentication for MP4 Format Container Using Subtitle Track

Lightweight Authentication for MP4 Format Container Using Subtitle Track

Vision Tracking: A Survey of the State-of-the-Art

Theoretical Analysis of Different Classifiers under Reduction Rough Data Set

Contact Info

Product

Resources

About