Abstract In this paper, a data hiding scheme is proposed which modifies the Absolute Moment Block Truncation Coding (AMBTC) technique to embed a large amount of secret data. This scheme employs a user-defined threshold value to classify the AMBTC compressed blocks as complex block and smooth block. In the case of smooth blocks, the bit plane is replaced with the secret data bits. Later, the quantization levels are re-calculated so that distortion is minimized. While for complex blocks, the bit plane is reconstructed in which every pixel is represented by two bits instead of just one bit. Now, the secret data is embedded into the first LSB of the bit plane. Finally, four new quantization levels are calculated for preserving the closeness of the resultant block to the original block. Thus, the proposed scheme is able to utilize each and every pixel of the cover image to hide the secret data while maintaining the image quality. This scheme achieves 1 bit per pixel data hiding capacity for every image. Experimental results show that our scheme is superior to the other existing schemes in terms of both hiding capacity and image quality.

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[20] Zhang Y., Guo S., Lu Z., and Luo H., “Reversible Data Hiding for BTC-compressed Images based on Lossless Coding of Mean Tables,” IEICE Transactions on Communications, vol. 96, no. 2, pp. 624-631, 2013. A High Capacity Data Hiding Scheme Using Modified AMBTC Compression Technique 155 Aruna Malik, received her B.Tech. in Computer Science and Engineering from Uttar Pradesh Technical University, Lucknow, India and M.Tech. in Computer Science and Engineering from National Institute of Technology, Jalandhar, Punjab, India. Currently, she is pursuing her doctoral degree in Computer Science and Engineering, at National Institute of Technology, Jalandhar, Punjab, India. Her research lies in the area of text and image based steganogrography, digital watermarking and image processing. Geeta Sikka, received her Ph.D in Computer Science and Engineering, from National Institute of Technology, Jalandhar, India. She did her Master’s degree in Computer Science from Punjab Agricultural University, Ludhiana. She is presently working as Associate Professor in the Department of Computer Science and Engineering at National Institute of Technology, Jalandhar. Her research interests are Software Engineering, Databases and Data mining. Harsh Verma, received his doctorate in Numerical Computing from Punjab Technical University Punjab, India. Currently, he is associate Professor in Computer Science and Engineering, National Institute of Technology, Jalandhar, India. His research interest includes in numerical computing, information security and computer networks. He has published various papers in national and international journal and conferences. He has attended various national and international workshop, training schools, and other technical activity during his academic carrier.