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Visual Cryptography project download with Source code



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This work focus on the spatial basis privacy method where message is hidden in the image by the change in the pixel value. So whole process is divide into two steps first is embedding where message which may be a text or image can be hide into the carrier image. Then second step is for receiver side which extracts data hiding information from the embedded image. Here encryption steps are so taken that it can save the originality of the carrier image.

This work centers around the digital picture invisible information concealing algorithm. Here entire work is isolate into embedding and extraction steps. For imperceptible embedding was done in such a manner that visiblity of the information hiding by naked eyes isn't conceivable. If there should be an occurrence of extraction information ought to be effectively recover from the received information with no data loss of the embedded information and in addition information. In Fig.  whole embedding block diagram is explained. While Fig.  whole extraction block diagram is explained.

Proposed work has developed a unique approach for protecting image and data under various attack conditions. Right now there have been numerous algorithms proposed for information concealing picture, video and sound. So this work focuses on transferring data by hiding in image. In this work carrier image was used to hide data where DWT feature actual region was utilized. Here proposed work has efficiently hide data in the carrier image while security of the carrier is also maintained. Here proposed work has efficiently hide data in the carrier image while security of the carrier is also maintained by embedding data in LL part of the image. In this step S vector obtained after inverse s-order is used where histogram of the image is find at one bins. In order to make reversible watermarking this work adopt histogram shifting method for watermarking in the image. Histogram shifting is obtained by manipulating the peak value with zero presence pixel value. 

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Software Requirement :   MATLAB

Hardware Requirement :   • Intel Processor 2.0 GHz or above. • 2 GB RAM or more. • 160 GB or more Hard Disk Drive or above.

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