Reversible data hiding for medical images using segmentation and prediction
|International Journal of Computer Science and Engineering|
|© 2019 by SSRG - IJCSE Journal|
|Volume 6 Issue 11|
|Year of Publication : 2019|
|Authors : A.Pushpa Athisaya Sakila Rani|
How to Cite?
A.Pushpa Athisaya Sakila Rani, "Reversible data hiding for medical images using segmentation and prediction," SSRG International Journal of Computer Science and Engineering , vol. 6, no. 11, pp. 70-77, 2019. Crossref, https://doi.org/10.14445/23488387/IJCSE-V6I11P115
Data hiding and embedding techniques assumes an important role to ensure safe and secure sharing of data in the modern era as data hacking is becoming very common. Unified data embedding and scrambling method along with reversible histogram shifting serve this purpose. Here the problem is once the embedded data is extracted the quality of the output image gets affected. In this study, Quad tree segmentation is used in segmentation of the image and neighborhood prediction method is used to embed data into a digital image in order to improve the quality of the output or reconstructed image. Prediction error is calculated and adjusted to minimum. The predicted pixels from the segmented image are vacated and the secret data pixels are inserted into those positions. The embedded image is extracted using reversible technique. The quality of the host image and the reconstructed image is measured by SSIM value. With the current experiment a SSIM value of 0.999is achieved for the reconstructed image.
DATA EMBEDDING, NEIGHBORHOODPREDICTION, RECONSTRUCTION, QTS,SSIM
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