COMPARATIVE STUDY OF HISTOGRAM SHIFTING ALGORITHMS FOR DIGITAL WATERMARKING

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1 International Journal of Computer Engineering and Applications, Volume X, Issue VII, July 16 ISSN COMPARATIVE STUDY OF HISTOGRAM SHIFTING ALGORITHMS FOR DIGITAL WATERMARKING Geeta Sharma and Vinay Kumar Department of Information Technology, Jagannath Institute of Management Sciences, Delhi ABSTRACT: Data hiding is a method of hiding or embedding secret data, called message, into a digital media, called cover; in such a way that message is unnoticeable to human eye. An algorithm that can retrieve the message from the cover without any loss to original image is called reversible. Histogram shifting has proven its importance in the field of digital watermarking after the work of Ni et al. In this paper, we will discuss about some variation of algorithms based on histogram shifting. We will further discuss about basis of our work. A multiple zero-peak points can be used for hiding the data in an efficient manner with histogram technique. Furthermore, hash will be created by using MD5 or SHA1. Keywords: Histogram, data hiding, spatial domain, transform domain, steganography, peak point, message digest, hash [1] INTRODUCTION Data hiding is a method of hiding or embedding secret data (called message) into a digital media (called cover) in such a way that message is unnoticeable to human eye. With increasing use of internet, need of data hiding arises to protect copyrights, and to authenticate the users of digital media. Although, one can use text, sound, images or videos as a cover, but due to its large number on the internet, images are most common form of cover. Generally the cover image is lost in the process of data hiding as it changes the pixel value of cover. An algorithm that can retrieve the message from the cover without any loss to original image is called reversible. Many techniques were proposed to serve this requirement. Broadly, these techniques can be classified as: 1. Spatial Domain Methods: There are many versions of spatial data hiding, all directly change some bits in the image pixel values in hiding data. Least significant bit (LSB)-based data hiding is one of the simplest techniques that hide a secret message in the LSBs of pixel values without introducing many perceptible distortions. Changes in the value of the LSB are imperceptible for human eyes.[2] Geeta Sharma and Vinay Kumar 13

2 COMPARATIVE STUDY OF HISTOGRAM SHIFTING ALGORITHMS FOR DIGITAL WATERMARKING 2. Transform Domain Technique: This is a more complex way of hiding information in an image. Various algorithms and transformations are used on the image to hide information in it. Transform domain embedding can be termed as a domain of embedding techniques for which a number of algorithms have been suggested [3]. Histogram shifting algorithm is a popular method of information hiding where a histogram is a graphical representation that is used to depict frequency of occurrence of data. According to Wikipedia, A histogram is a graphical representation of the distribution of numerical data. It is an estimate of the probability distribution of a continuous variable. Figure 1 (Courtesy: Wikipedia) It is an extremely useful technique in image processing. It is an estimate of the probability distribution of a continuous variable and was first introduced by Karl Pearson. Histograms are also used to study distribution of various components of the images [1]. In this method, a bin size is specified and used for standard sizing of data. According to Wikipedia, an image histogram is a type of histogram that acts as a graphical representation of the tonal distribution in a digital image. In histogram shifting, histogram is shifted towards right or left. If we add or subtract some constant value from the histogram then a clear change in brightness can be seen in the image. Following is the example of a standard image Lighthouse.jpg in Figure 2 and its histogram is displayed in Figure 3. This histogram is generated through an online histogram generator

3 International Journal of Computer Engineering and Applications, Volume X, Issue VII, July 16 ISSN Figure 2 (LightHouse.jpg) [2] LITERATURE REVIEW Figure 3 (Histogram of LightHouse.jpg) The idea of reversible histogram based data hiding was first proposed by Ni et al in 2004 [4]. It forms the basis for histogram shifting data hiding. In this method, first a zero point and a peak point are found. Here, zero point is the smallest value of the pixels. This gray scale zero value is not a part of the cover image. Whereas, peak point is a value that has maximum number of pixels, in the cover image. The payload capacity of the cover image is dependent on the peak point and for increasing the payload capacity; a number of zero-peak pairs are used. The point in the histogram next to peak value is shifted one position to the right. A vacancy is created there. All points next to this are also shifted one position and the point near zero point gets shifted into the zero point. Now the peak point and the vacant position near it are used for embedding the watermark bits. For embedding more data this is repeated again and again. All the embedding algorithms that are listed below use multiple pairs of maximum and minimum points i.e. multiple-zero-peak-points. There are a number of methods for histogram shifting: a. Histogram shifting Algorithm with Multiple Pairs of Peak and Zero Points: In this section, we will discuss another algorithm by Ni et al proposed in 2006 [5]. In this algorithm, the case of three pairs of peak and zero points, a pseudo code embedding algorithm is presented. It is designed to generate this code to reach the cases where any number of multiple pairs of peak and zero points are used. Embedding process and extracting process are the two processes of this algorithm. b. Histogram shifting Algorithm Using Predictive Coding: This scheme is proposed by Tsai et al in 2009[6]. It based the likeness of neighboring pixels in the cover. By using the prediction technique and the residual histogram of the predicted errors of the host image, the secret data is embedded in the residual image by using a modified histogram-based approach. To increase the hiding capacity of the histogram-based scheme, the linear prediction technique is employed to process the image. Here, the pixels of the image are predicted from the residual image. Secret data are then embedded in the residual image by using a modified histogram-based approach. The proposed scheme consists of two procedures: the embedding procedure and the extraction and image restoration procedure.[7] Geeta Sharma and Vinay Kumar 15

4 COMPARATIVE STUDY OF HISTOGRAM SHIFTING ALGORITHMS FOR DIGITAL WATERMARKING c. Histogram Modification algorithm for Difference Images: Chia-Chen Lin et al in 2008 has proposed another method of histogram based data hiding technique. In this scheme which is based on the difference image histogram modification, the peak point is used to hide secret messages. This method is divided into three phase: Difference histogram creating, hiding and extracting phases[7]. This algorithm has been base for many other algorithms. d. Histogram shifting Algorithm Based on Three-Pixel Block Differences: In this section we will consider, a data hiding scheme has been proposed by Ching-Chiuan Lin et al in It embeds a message into an image using the two differences, between the first and the second pixels as well as between the second and the third pixels in a three-pixel block. [7] Histogram is not directly used in this method, rather its fundamental concepts have been indirectly applied, and that is using peak points, zero points and shifting the gray scale between these two values. In the cover image, an absolute difference between a pair of pixels is selected to embed the message. In the best case, a three-pixel block can embed two bits and only the central pixel needs to be increased or decreased by 1. First an image is divided into non-overlapping three-pixel blocks, where the maximum and minimum allowable pixel values are 255 and 0, respectively [7]. e. Histogram shifting Algorithm for JPEG2000 images: This method is proposed by Zhe-Ming Lu et al in It was designed for JPEG2000 format. The high frequency subbands of the cover image are divided into blocks. Then the histogram shifting method was applied to the histogram of the block of embedding data. Every coefficient that is associated with the peak point embeds two bits of data. A direction sign is used to shift the histogram left of right. f. Histogram shifting Algorithm Based on Correlation between Sub-sampled Images: In this scheme, a data hiding method is described which has been proposed by Kim [8] that modifies the difference histogram between sub-sampled images. This scheme is based on the application of the spatial correlation in neighboring pixels in order to achieve higher capacity while comparing with other histogram based methods. It also has two phases embedding process and extracting process. [3] METHOD PROPOSED We are working on a reversible data hiding algorithm for digital water marking. Watermarking is a technique which allows an individual to add hidden copyright notices or other verification messages to digital audio, video, or image signals and documents[2]. A hash of hidden message will be first created using MD5. The MD5 message-digest algorithm produces a 128-bit (16-byte) hash value, and it is generally written as a 32 digit hexadecimal number in text format. MD5 has been used in a great 16

5 International Journal of Computer Engineering and Applications, Volume X, Issue VII, July 16 ISSN number of cryptographic applications, and it is commonly used to variations and to verify data integrity [2]. Now, to hide the 128-bit hash value, we will create various blocks on the image. Image will be either JPEG or BMP and it will serve as the cover for our message. Histogram shifting directly works on the pixel and thus gives us more powerful and easy solution. The cover image is properly protected and a better way to predict pixels is possible. It is a robust way through which extractor can easily restore the same source image without any loss to the data. As discussed above, a multiple zero-peak points enhance the efficiency of the histogram. It considerably enhances the capacity of the image to hide information. [4] CONCLUSION There are many methods used by the researchers to hide the data to protect data against unauthorized replication to protect commercial and intellectual interest of the creator. Since its invention or embedding, the histogram-bin shifting technique has proven its importance in the field of digital watermarking. To provide the good security these algorithm are vulnerable because of inherent flaws due to applied checksum approach. Moreover, the main issues with the previous steganography technology are robustness, imperceptibility and all file formats acceptability. [2] A comparatively more robust and imperceptible approach is required to be explored. REFERENCES [1] M.Aarthy, P.Sumathy. : A COMPARISON OF HISTOGRAM EQUALIZATION METHOD AND HISTOGRAM EXPANSION. International Journal of Computer Science and Mobile Applications, Vol.2 Issue. 3, March- 2014, pg ISSN: [2] Geeta Sharma, Vinay Kumar. : Principle of Reversible Information Hiding for Watermarking. International Conference on Recent Development in Engineering, Science and Management 15 [3] The GIS Spatial Data Model. ESRM 250, The University of Washington Spatial Technology, School of Forest Resources. 20th April < [4] Shi, Y.Q., Ni, Z., Zou, D., Liang, C., Xuan, G.: Lossless Data Hiding: Fundamentals, Algorithms and Applications. In: Proc. IEEE Int. Symp. Circuits Syst., Vancouver, BC, Canada, vol. II, pp (May 2004) [5] Ni, Z., Shi, Y.-Q., Ansari, N., Su, W.: Reversible Data Hiding. IEEE Transactions on Circuit and Systems for Video Technology 16(3) (March 2006) [6] Tsai, P., Hu, Y.-C., Yeh, H.-L.: Reversible Image Hiding Scheme Using Predictive Coding and Histogram Shifting. Signal Processing 89, (2009) [7] Yasaman Zandi Mehran, Mona Nafari,Alireza Nafari, and Nazanin Zandi Mehran : Histogram Shifting as a Data Hiding Technique: An Overview of Recent Developments. DICTAP 2011, Part I, CCIS 166, pp , [8] Kim, K.-S., Lee, M.-J., Lee, H.-Y., Leea, H.-K.: Reversible Data Hiding Exploiting Spatial Correlation Between Sub-sampled Images. Pattern Recognition 42, (2009) Geeta Sharma and Vinay Kumar 17

6 COMPARATIVE STUDY OF HISTOGRAM SHIFTING ALGORITHMS FOR DIGITAL WATERMARKING Author[s] brief Introduction Dr. Vinay Kumar is working as a Professor in VIPS, Vivekanand school of information technology, Pitampura, Delhi. Before joining VIPS, he was working as a Scientist in National Informatics Center, MoCIT, Government of India. He has authored a book on Discrete Mathematics. His area of interest is graph algorithm, steganography, discrete mathematics, data security and privacy. Geeta Sharma is working as an Associate Professor in Jagannath Institute of Management Studies, Rohini, Delhi. Her area of interest is steganography, digital watermarking, data security and DBMS. 18