An Efficient Watermarking and Key Generation Technique Using DWT Algorithm in Three-Dimensional Image
R. Saikumar1, D. Napoleon2
1R. Sai Kumar, Research Scholar Department of Computer Science Bharathiar University, Coimbatore, (Tamil Nadu), India.
2Dr. D. Napoleon, Assistant Professor Department of Computer Science Bharathiar University,
Coimbatore, (Tamil Nadu), India.
Manuscript received on 12 March 2019 | Revised Manuscript received on 19 March 2019 | Manuscript published on 30 July 2019 | PP: 2360-2365 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2650037619/19©BEIESP | DOI: 10.35940/ijrte.B2650.078219
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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: Discrete Wavelet Transform is the algorithm which can be used to increase the contrast of an image for better visual quality of an image. The histogram value for original image with highest bins is taken for embedding the data into an image to perform the histogram equalization for repeating the process simultaneously. Information can be embedded into the source image with some bit value, for recovering the original image without any loss of the pixels. DWT is the first algorithm which has achieved the image contrast enhancement accurately. This approach maintained the original visual quality of an image even though themessage bits are embedded into the contrast-enhanced images. The proposed work with an original watermarking scheme based on the least significant bit technique. As a substitute of embedding the data into a simple image as watermarking, least significant bitmethod by utilizing the three wavelets transform is applied in the proposed system in order to enhance the embedding technique using spatial domain. For security, the Huffman coding has used to secure the data embedded into a host image, which can convert the secret message sequence into bit sequence for least significant bit operation. DWT can analyze the signal at multiple resolutions and it can divide the image into two types of quadrants as high and low-frequency quadrants. Here dividing an image into low and high it makes the information to hide.
Index Terms: DWT; Digital Image Processing; Huffman Coding; Watermarking.

Scope of the Article: Next Generation Internet & Web Architectures