Image Steganography using Improved Lsb-Mapping Technique with Enhanced Recovery Speed
Shyla. M.K1, K.B.Shivakumar2, Rajendra Kumar Das3
1Shyla.M.K, Department of Electronics and communication, SSIT Tumakuru, Karnataka, India.
2Dr.K.B.Shivakumar, Department of Tele-communication, SSIT Tumakuru, Karnataka, India.
3Dr.Rajendra kumar Das, Principal, DRIEMS, Tangi, Cuuttok, Odisha, India.
Manuscript received on November 11, 2019. | Revised Manuscript received on November 20 2019. | Manuscript published on 30 November, 2019. | PP: 11473-11478 | Volume-8 Issue-4, November 2019. | Retrieval Number: B3701078219/2019©BEIESP | DOI: 10.35940/ijrte.B3701.118419
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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: In recent days, for sending secret messages, we require secure internet. Image steganography is considered as the eminent tool for data hiding which provides better security for the data transmitted over internet. In the proposed work, the payload data is embedded using improved LSB-mapping technique. In this approach, two bits from each pixel of carrier image are considered for mapping and addition. Two bits of payload data can be embedded in one cover image pixel hence enhanced the hiding capacity. A logical function on addition is applied on 1st and 2nd bits of cover image pixel, and a mapping table is constructed which gives solution for data hiding and extraction. Simple addition function on stego pixel is performed to extract payload data hence increases the recovery speed. Here the secret data is not directly embedded but instead mapped and added with a number using modulo-4 strategy. Hence the payload data hidden using proposed approach provide more security and it can resist against regular LSB decoding approaches. The proposed work is implemented and tested for several gray scale as well as color images and compared with respect to parameters like peak signal to noise ratio and MSE. The proposed technique gives better results when compared and histogram of cover and stego images are also compared.
Keywords: Addition Function, LSB Mapping, Mapping Table and Recovery Speed.
Scope of the Article: Logic, Functional programming and Microcontrollers for IoT.