Mobile and Intelligent Sensing for Video Watermarking Using Spectral Centroid and Haar Wavelet Transformation on High Performace Computing

Some technologies are technologically advanced to provide security from illegal copying. Two complementary methods are encryption and watermarking. Encryption safeguards the information throughout the communication from the sender to the receiver. The data might present a distorted image after receipt and subsequent decryption. Watermarking complements encryption through embedding data openly into the image. Therefore, the watermark continuously remains existing in the data. A digital watermark is a category of indication secretly entrenched in a noise-tolerant signal similar to audio or else image information. It is indeed applied to distinguish copyright possession of such signal. Computer-aided hiding of the given digitized information in a carrier is known as watermarking. Digital watermarks possibly will be employed to validate the authenticity or integrity of a carrier signal or to determine source uniqueness. It is evidently applied for determining copyright contraventions and aimed at banknote verification. Analogous to traditional watermarks, digital watermarks are unique only beneath certain conditions. Once a digital watermark varies a carrier in a manner that it turns out to be noticeable, formerly it is of no use. The media will be visible by traditional watermarks (similar to images or else video) but the signal might be pictures, video, audio, texts or 3D models in digital watermarking. A signal can transmit some different watermarks at the equivalent time. Image watermarking is achieved in this study using two methods known as Hidden Markov Tree–Contourlet Wavelet Transform (HMT-CWT) and Haar wavelet transform – Discrete Fourier transform (HWT-DFT). In the next HWT-DFT method, a video is given as an input and it is split into two halves (audio and image). The audio is de-watermarked through Spectral Centroid Wavelet Transform and enhanced by utilizing Firefly procedure. The images is handled through HWT in addition to DFT. Then the output watermarked images and audio combined together to form a watermarked video. The obtained video is de-watermarked to produce the original copy of the video. The process of getting back the original copy by removing the watermark from the video is called as de-watermarking.