Developing an efficient digital image watermarking for smartphones


As of late, Smartphone utilization has been expanding quickly to the point where it outperformed all other electronic gadgets. Mixed media sharing and Image/Video catching are among the most used functionalities of cell phones. Cell phones and Internet accessibility made the catch, transmission and capacity of advanced information simple and advantageous. The straightforwardness, availability, and solid abilities of such gadgets make it difficult to secure the protection and Intellectual Property (IP) of advanced sight and sound. While a wide range of advanced sight and sound are in danger, computerized pictures are seriously influenced.


Altering and changing over advanced pictures should be possible effectively, and henceforth securing them turns out to be considerably harder. Advanced picture watermarking is a system used to validate and secure the IP of computerized pictures. In this project we propose a productive and adaptable computerized watermarking framework that keeps running on Android gadgets. The framework utilizes RAW pictures (an element of the latest Android programming, called Lollipop) to implant a watermark at a beginning time before any alteration and transformation of the picture. The framework consolidates open key cryptography for expanded insurance. A basic and powerful watermarking method is used for productivity. Other watermarking procedures are offered for adaptability. At last, the framework utilizes the inborn highlights of the Android working framework to keep running in parallel and be accessible to different applications.


his paper proposes a continuous and vitality effective picture watermarking plan utilizing DCT – DWT crossover change. The proposed strategy is utilizing a 2 – level of quantization on the segment of genuine nature picture caught continuously and low recurrence band coefficients are chosen for the dataset arranged of size 256 * 10 utilizing these coefficients, which is provided to Outrageous Learning Machine (ELM) a solitary layer feed forward system. A standardized section vector of size 256 * 1 is produced by ELM for its use as key arrangement for implanting the watermark. This half and half changes give a superior indistinctness and decrease in the time taken by whole watermarking process i.e. inside a second, makes it vitality effective and reasonable for the proposed advanced mobile phone android application for a constant picture watermarking.


CPU type : Intel Pentium 4

Clock speed : 3.0 GHz

Ram size : 512 MB

Hard disk capacity : 40 GB

Monitor type : 15 Inch shading screen

Keyboard type : web console



Working System: Android Studio

Language : ANDROID SDK 7.0

Documentation : Ms-Office

BASE PAPER: Developing an efficient digital image watermarking for smartphones

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