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You are here: Home / ieee projects 2013 / Pixel Prediction Based on Image Inpainting

Pixel Prediction Based on Image Inpainting

January 27, 2014 by IeeeAdmin

Reversible steganography, also called reversible data hiding, has been studied extensively in recent years,especially for digital images . The property of reversibility means that the original form of the image, before the secretbits were embedded, can be recovered completely after the embedded bits are extracted. Reversible data hiding can be used for medical, military, and legal applications, which do not allow any modification in the digital representation of the cover image due to the risk of misinterpretations. Tian proposed a reversible data hiding method based on difference expansion. The cover image was divided into a series of non overlapping, neighboring pixel pairs, and the difference of each pixel pair was doubled. Then, the doubled difference was either kept reserved or modified according to the parity of the embedding secret bit. On the receiver side, the embedded secret data can be extracted easily from the least significant bit (LSB) of the differences of the pixel pairs in the stego image. a method based on histogram shifting to embed secret data reversibly. The peak point of the image histogram was selected and the pixel values in the range from its right one to the zero point were increased by one to create one vacant histogram bin for embedding. The number of secret bits that could be embedded depended on the pixel number of the peak point in the histogram. The information of the peak point and zero point was required in the procedure of extracting the embedded data and recovering the cover image. In our scheme, fewer reference pixels are chosen in the smooth regions of the cover images, while more reference pixels are chosen in the complex regions. This strategy of choosing reference pixels can produce a greater number of possible embeddable pixels and avoid more distortion caused by the embedding procedure. According to the chosen reference pixels, the PDE-based inpainting algorithm can effectively generate the prediction image that has the similar structural and geometric information as the cover image

Filed Under: ieee projects 2013 Tagged With: ieee projects 2015 for be cse, IEEE Projects 2015 For BTECH CSE, IEEE Projects 2015 for Mca, ieee projects 2015 for me cse

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