Improved Data Hiding Scheme using VQ based Index Map Compression and Codebook Extension
P. Uma1, S. Vimala2
1P. Uma*, Research Scholar, Department of Computer Science, Mother Teresa Womens University, Kodaikanal, India.
2S. Vimala, Associate Professor, Department of Computer Science, Mother Teresa Women‟s University, Kodaikanal, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 25, 2020. | Manuscript published on March 10, 2020. | PP: 801-807 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2547039520/2020©BEIESP | DOI: 10.35940/ijitee.E2547.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Now-a-days, data protection has become inevitable for confidential transactions that happen over net. Transmission of such confidential data has become a challenging issue in today’s scenario. Many Data Hiding techniques are used for transmitting data in a secured way. The secret data can be hidden as part of any type of file such as Text file, Sound file, image file, Video file, etc. It has been proposed to hide secret data as part of cover image. The proposed work adopts Vector Quantization (VQ) which is one of the powerful and simple image compression techniques to compress the size of the cover image and to reduce the cost associated with storage/transmission. VQ transforms the cover image into its corresponding Codebook and Index Map. The confidential data is then embedded as part of the Codebook and Index Map. The proposed method helps in improving the performance by increasing the embedding capacity and coding efficiency. The performance of Steganography is improved in three levels. The embedding capacity of the proposed method is increased by 23,726 bits when compared to that of existing similar methods, which is a significant improvement.
Keywords: Data hiding, Embedding Capacity, Steganography, Vector Quantization
Scope of the Article: Data Analytics