Privacy Protection of Medical Data using Histogram Shifting Based Reversible Data Hiding

Privacy Protection of Medical Data using Histogram Shifting Based Reversible Data Hiding

K. Meena

II-ME (Communication systems) Jayaram College of Engineering and Technology

Trichy, India

R. Suresh Kumar Assistant professor (ECE)

Jayaram college of Engineering and Technology Trichy, India

Abstract The project presents privacy protection of medical images with information using histogram shifting based reversible data hiding. An Embedding module involves image encoding and histogram shifting based difference expansion. First of all, the patients' privacies need to be preserved. Therefore, embedding secret data into the medical images would be one of the useful methods for protecting the privacies. Next, because external data are hidden into the original image, some alterations are supposed to be induced. After data embedding, the output image should be as similar as its original counterpart and medical doctors may lead to proper treatment by using the images with hidden data when necessary. Reversible data hiding is a newly developed branch in data hiding or watermarking researches. Reversibility means the hiding data and host image recovered without any distortion. Later on, the medical image containing data might be retrieved by medical doctors while necessary and both the original image and the hidden data can be perfectly recovered with the algorithm corresponding to the embedding scheme. Finally Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) will be used to evaluate the final performance

Keywords Embedding performance, Histogram Shifting (HS), Reversible Data Hiding (RDH), Steganography.

1. INTRODUCTION

   Recently, data hiding has played an important role in protecting (or securing) sensitive data. Most data hiding techniques perform data embedment by altering the contents of a host media. As a result, the host image cannot be completely restored after the data extraction. These types are called irreversible data hiding techniques. To maintain the originality of host image or signal, particularly those associated with, medical and military fields and media with geographic information, reversible data hiding techniques are used. Reversible data hiding, also known as lossless data hiding, enables the recovery of both the original host media and the secret message from the stego-images. Some of the data hiding methods are given below.

   The Internet serves as an important role for data sharing. In that some confidential data might be copied, stolen, modified, or even destroyed by an intruder. Therefore, security

   problems become an important issue. Though encryption provides certain security, they make the secret messages meaningless. These meaningless or unnatural messages usually attract intruder attention. To avoid that new security approach arises called Steganography. Steganography is used to hiding the secret data into another transmission medium to achieve secret communication. It increase the security, does not replace cryptography. For most image data hiding methods, the host image is permanently distorted and it cannot be restored from the host image or content. But in some applications such as medical and military fields any distortion due to data embedding is intolerable and the availability of the original image is in high required. Reversible Data hiding (RDH) is one of the solutions for that, in which the host image can be fully restored after data embedding. Its possibility is mainly due to the lossless compressibility of host images.

2. STEGANOGRAPHY

   Steganography is the art and science of hidden messages in such a way that no one, apart from the sender and receiver, suspect the existence of the information. It means "concealed writing." The hidden messages will appear to be (or be part of) something else: secret messages, images, articles, any lists, or some other cover text. For example, the hidden message appears to be invisible ink between the visible lines of a private letter.

   III .TECHNIQUES

   Steganography has been widely used in historical times and the present day. Some examples are Hidden messages within wax tablets in ancient Greece, people wrote messages on the wood, and then covered it with wax upon which an innocent covering message was written.

   1. Difference Expansion Techniques

      In difference Expansion (DE) technique are used to derive high capacity, low-distortion reversible data hiding. This technique divided the image into pairs of pixels, and a secret message was embedded into the difference between the pixels of each pair that was not expected to cause overflow/ underflow issues. Simulation showed that the payload size

      and the perceived quality of the marked images generated by this technique were better than those achieved by the existing method.

   2. LSB based data hiding

   One of the earliest data embedding methods is the LSB (least significant bit) modification. In this well-known method, the LSB of each signal sample is replaced (over- written) by a payload data bit. During extraction, these bits are read in the same scanning order, and payload data is reconstructed.

   1. DATA EMBEDDING

      Fig.1. Block Diagram of Data Embedding

      1. Input Image

         In imaging science, image processing is any form of signal processing for which the input is an image, such as a photograph or video frame

      2. Image Histogram

         An image histogram is a type of histogram that acts as a graphical representation of the tonal distribution in an image. Image histograms are present on many modern cameras. The histogram plots the number of pixels in the image (vertical axis) with a particular brightness value (horizontal axis).

      3. Histogram Shifting

         In this method, peak of image histogram is utilized to embed data. In that certain pixels are used to create vacant spaces, some other pixels are used to carry hidden data to fill those vacant spaces.

      4. Encoding Process

      Here Run length encoding is used to reduce redundant pixel values in an image. The advantages of RLE encoding are that its, in principle, very easy to comprehend and implement compared with other compression techniques used today. However, the compression results depend heavily upon the input. In the best case, RLE can reduce data to merely two numbers if all the values in the original data are exactly the same, regardless of the size of the input. Another advantage of RLE is a lossless (or reversible) compression technique.

      E .Encryption

      Chaos encryption is one of the advanced encryption standard to encrypt the privacy data for secure transmission. It encrypts the original text datas with encryption key value generated from chaotic sequence. Here logistic map is used for generation of chaotic map sequence. It is very useful to transmit the secret data through unsecure channel securely which prevents data hacking.

      F. Embedding Process

      Consider an image I. select an integer a from 1 a 253, the embedded image I get into the following way.

      Ii, j 1, if Ii, j < a Ii, j m, if Ii, j = a

      Ii, j + m, if Ii, j = a + 1 Ii, j + 1, if Ii, j > a + 1

      Where (i, j) is a pixel value and m {0, 1} is a data bit to be embedded.

   2. DATA EXTRACTION

      Fig.2. Block Diagram of Data Extraction

      1. Data Extraction

         The extracted image I1 get into the following way.

         1. If Ii, j < a 1, there is no hidden data and its original value is Ii, j + 1.

         2. If Ii, j {a 1, a}, the pixel is ued to carry hidden data and its original value is a. The embedded data bit is m = a Ii, j.

         3. If Ii, j {a + 1, a + 2}, the pixel is used to carry hidden data and its original value is a+1. The embedded data bit is m = Ii, j – (a + 1).

         4. If Ii, j > a+2, there is no hidden data and the original value is Ii, j -1.

      2. Decoding

         It is a very simple form of data compression in which runs of data (that is, sequences in which the same data value occurs in many consecutive data elements) are stored as a single data value and count, rather than as the original run. This is most useful on data that contains many such runs: for example, simple graphic images such as icons, line drawings.

      3. Reversible Data Hiding (RDH)

         The original cover can be losslessly restored after the embedded information is extracted. As is known, a RDH algorithm usually depends on some parameters (e.g., the

         integer a defined) and these parameters should be communicated to decoder. In some applications, even any degradation of the original cover is not allowed, such as medical imagery, military imagery and law forensics so Reversible Data Hiding needed.

   3. RESULTS

In this section the experimental results of the method based on two techniques to evaluate the hiding performance. First one is the capacity of hiding data and another one is the imperceptibility of the stego image, also called the quality of stego image.

Fig.3. Input Image

Fig.4.Shifting Level

Fig.5. Histogram of an Input Image

Fig.6. Histogram Shifted Image

Fig.7. Secret message

Fig.8.Encrypted message

Fig.9. Selected Secret Message

Fig.10. Embedded Image

Fig.11. Reconstructed Image

Fig.12. Performance analysis

VI .CONCLUSION

The work dealt with the techniques for a new and efficient steganographic method for embedding secret messages into images without producing any major changes has been proposed. Using this method we can extract the original image from sago image with less distortion. Using this method we also can increase a hiding capacity

ACKNOWLEDGEMENT

First and foremost I thank God, the almighty who stands behind and strengthens me to complete the paper successfully.

I take this opportunity to express my profound gratitude to Mr. R. SURESH KUMAR, M.E., Assistant Professor, ECE, internal guide for his encouragement and help rendered to me for the completion of my project.

I am very much thankful to my parents and my friends whose consistent encouragement, moral support and blessings made to finish this paper.

REFERENCES

1. Xiaolong Li, Bin Li, Bin Yang, and Tieyong Zeng,

   General Framework to Histogram-Shifting-Based Reversible Data Hiding, IEEE Transactions On Image Processing, Vol. 22, No. 6, June 2013

2. R. Caldelli, F. Filippini, and R. Becarelli, Reversible watermarking techniques: An overview and a classification, Eur. Assoc. Signal Process. J. Inf. Security, vol. 2010, no. 2, pp. 119, 2010.

3. G. Coatrieux, C. L. Guillou, J. M. Cauvin, and C. Roux, Reversible watermarking for knowledge digest embedding and reliability control in medical images, IEEE Trans. Inf. Technol. Biomed., vol. 13, no. 2,pp. 158165, Mar. 2009.

4. S. Lee, C. D. Yoo, and T. Kalker, Reversible image watermarking based on integer-to-integer wavelet transform, IEEE Trans. Inf. Forens. Security, vol. 2, no. 3, pp. 321330, Sep. 2007.

AUTHORS PROFILE

K.MEENA received the B.E. degree in Electronics and Communication Engineering from the Sona College of Technology, Salem, Anna University, Chennai, India, in 2012, the M.E degree in Communication Systems from the Jayaram College of Engineering & Technology, Trichy, Anna University, Chennai, India, in 2014. Her research interest includes Digital Image Processing and Medical Electronics.

R. SURESH KUMAR received the B.E. degree in Electronics and Communication Engineering from the TPGIT Vellore, Anna University, Chennai, India, in 2006, the M.E degree in Applied Electronics from the PSG college of technology, Coimbatore, Anna university Chennai, India, in 2009. Currently working as Assistant professor in Jayaram College of Engineering & Technology, Trichy, India. His research interest includes Digital Image Processing ,VLSI Design, Embedded Systems.