Billions of physical gadgets are by and by associated with the Internet molding the Internet of Things (IoT). These gadgets are making a more proportion of helpful or pointless data. The transmission and getting ready of this data is a trying errand. Diverse IoT applications and future research bearing are in like manner talked. One of the unquestionable application parts of IoT framework is in the Security Sector. It is basic to an uncommon negligible exertion answer for check wrongdoing and assurance security to people from the home, military, business, and so on. This paper using Raspberry Pi IoT establishment includes the portrayal driven progression process for AI Security System. It remarks the livelihoods of client end demand, for instance, to securely transmit information through the layers of IoT designing. It goes for giving a low-control, monetarily sense and normal IoT dependent on security AI system which helps proximity ID, unmistakable 98% evidence and confirmation of pariahs. The course of action makes usage of USB Webcam as an image getting unit, electric entryway hit as an actuator which gives application programming interfaces (APIs) to collect game plans which is flawless with IoT foundation of improvement for video steganography distribution for Raspberry Pi.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Barrios JM, Bustos B (2011) Competitive content-based video copy detection using global descriptors Springer Science+Business Media. Multimed Tools Appl. https://doi.org/10.1007/s11042-011-0915-x
Batioua I, Benouini R, Zenkouar K, El-Fadili H (2017) Image analysis using new set of separable two-dimensional discrete orthogonal moments based on Racah polynomials. EURASIP J Image Video Process 2017:20. https://doi.org/10.1186/s13640-017-0172-7
BenHajyoussef A, Ezzedine T, Bouallègue A (2017) Gradient-based pre-processing for intra prediction in High Efficiency Video Coding. EURASIP J Image Video Process 2017:9. https://doi.org/10.1186/s13640-016-0159-9
Cai Y, Lu Y, Kim SH, Nocera L, Shahabi C (2017) Querying geo-tagged videos for vision applications using spatial metadata. EURASIP J Image Video Process 2017:19. https://doi.org/10.1186/s13640-017-0165-6
Domingos PM (2012) A few useful things to know about machine learning. Commun ACM 55(10):78–87
Esmaeili MM, Fatourechi M, Ward RK (2011) A robust and fast video copy detection system using content-based fingerprinting. IEEE Trans Inf Forensics Secur 6(1):213–226
Haitsma J, Kalke T (2012) A highly robust audio fingerprinting system. In Proceedings of the International Symposium on Music Information Retrieval. pp 107–115.
Jawed A, Das A (2015) Security Enhancement in audio steganography by RSA algorithm. Int J Electron Commun Technol (IJECT) 6(1):1
Jiang M, Tian Y, Huang T (2012) Video copy detection using a soft cascade of multimodal features. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME’12). pp 374–379.
Karthika P, Vidhya Saraswathi P (2017a) A survey of content based video copy detection using big data. Int J ScI Res Sci Technol 3(5):114–118
Karthika P, Vidhya Saraswathi P (2017b) Content based video copy detection using frame based fusion technique. J Adv Res Dyn Control Syst 9(17):885–894
Karthika P, Vidhya Saraswathi P (2019) Digital video copy detection using steganography frame based fusion techniques. In: Pandian D., Fernando X., Baig Z., Shi F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture notes in computational vision and biomechanics, vol 30. Springer, Cham. Doi: 10.1007/978-3-030-00665-5_7
Kotenko I, Saenko I, Skorik F, Bushuev S (2015) Neural network approach to forecast the state of the internet of things elements. In Soft Computing and Measurements (SCM), 2015 XVIII International Conference on, pp 133–135, May 2015.
Lei Y, Luo W, Wang Y, Huang J (2012) Video sequence matching based on the invariance of color correlation. IEEE Trans Circuits Syst Video Technol 22(9):1332–1343
Lin PY, You B, Lu X (2017) Video exhibition with adjustable augmented reality system based on temporal psycho-visual modulation. EURASIP J Image Video Process 2017:7. https://doi.org/10.1186/s13640-016-0160-3
Liu H, Hong Lu, Xue X (2013) A segmentation and graph-based video sequence matching method for video copy detection. IEEE Trans Knowl Data Eng 25(8):1706–1718
Lixin L, Bian H, Shao G (2013) An effective wavelet-based scheme for multi-focus image fusion. In IEEE International Conference on Mechatronics and Automation (ICMA), 2013.
Mahmoud R, Yousuf T, Aloul F, Zualkernan I (2015) Internet of things (IoT) security: Current status, challenges and prospective measures. In 2015 10th International Conference for Internet Technology and Secured Transactions (ICITST), pp 336–341, Dec 2015.
Nan N, Liu G (2015) Video copy detection based on path merging and query content prediction. IEEE Transactions On Circuits And Systems For Video Technology, 25(10)
Negnevitsky M (2011) Artificial intelligence: a guide to intelligent systems. Pearson, 2011.
Phamila YAV, Amutha R (2014) Discrete cosine transform based fusion of multi-focus images for visual sensor networks. Signal Process 95:161
Prakash O, Srivastava1 R, Khare A (2013) Biorthogonal wavelet transform based image fusion using absolute maximum fusion rule. Proceedings of 2013 IEEE Conference on Information and Communication Technologies (ICT) 2013.
Sharmila K, Rajkumar S, Vijayarajan V (2013) Hybrid method for multimodality medical image fusion using discrete wavelet transform and entropy concepts with quantitative analysis. In International conference on Communication and Signal Processing (ICCSP), IEEE, April 3–5, 2013.
Singh VK, Mukhopadhyay S, Xhafa F et al (2020) A budget feasible peer graded mechanism for IoT-based crowdsourcing. J Ambient Intell Human Comput 11:1531–1551. https://doi.org/10.1007/s12652-019-01219-z
Song J, Yang Yi, Huang Zi, Shen HT, Hong R (2013) Multiple feature hashing for large scale near-duplicate video retrieval. IEEE Trans Multimedia 15(8):1997–2008
Sung BY, Lin CH (2017) A fast 3D scene reconstructing method using continuous video. EURASIP J Image and Video Process 2017:18. https://doi.org/10.1186/s13640-017-0168-
Tasdemir K, Enis Cetin AE (2014) Content-based video copy detection based on motion vectors estimated using a lower frame rate, In Proceedings of Signal Image and Video Processing, Springer, pp 1049–1057
Vidhya Saraswathi P, Venkatesulu M (2013) A secure image content transmission using discrete chaotic maps. Jokull J 63(9):404–418
Xingmei X, Jing Z, He W (2013) Research on the basic characteristics, the key technologies, the network architecture and security problems of the internet of things. In Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on, pp 825–828, Oct 2013.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Karthika, P., Vidhya Saraswathi, P. IoT using machine learning security enhancement in video steganography allocation for Raspberry Pi. J Ambient Intell Human Comput (2020). https://doi.org/10.1007/s12652-020-02126-4
- Machine learning framework
- Artificial intelligence
- Raspberry Pi
- USB webcam