Adaptive Steganography using 3D Color Texture Feature
P. Pavan Kumar1, L.Suneel2, Nagaraja Kumar Pateti3, A.M. Srinivasacharyulu4
1P. Pavan Kumar, Associate Professor, Department of Electronics and Communication Engineering, CMR Institute of Technology, Hyderabad (Telangana), India.
2L.Suneel, Assistant Professor, Department of Electronics and Communication Engineering, CMR Institute of Technology, Hyderabad (Telangana), India.
3Nagaraja Kumar Pateti, Assistant Professor, Department of Electronics and Communication Engineering, CMR Institute of Technology, Hyderabad (Telangana), India.
4A.M. Srinivasacharyulu, Assistant Professor, Department of Electronics and Communication Engineering, CMR Institute of Technology, Hyderabad (Telangana), India.
Manuscript received on 06 September 2019 | Revised Manuscript received on 15 September 2019 | Manuscript Published on 26 October 2019 | PP: 299-302 | Volume-8 Issue-11S2 September 2019 | Retrieval Number: K104709811S219/2019©BEIESP | DOI: 10.35940/ijitee.K1047.09811S219
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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: Human vision framework is commonly an emotional recognition which differs according to people. Intricacy of a picture assumes huge job while verifying information in to it. In this paper another steganography approach is introduced which uses joined 3D Color Texture Feature (CTF) to distinguish complex districts of picture for information stowing away so visual assault to identify shrouded message turns out to be very testing. Recurrence area is utilized to shroud the information in these chose complex areas by means of Discrete Cosine Transform (DCT). These sorts of zones are initially boisterous and separating additional data is difficult. Each picture has diverse multifaceted nature levels and spatial districts, and since information covering up is legitimately reliant on it, so the steganography framework ends up versatile. The outcome demonstrates that proposed versatile strategy gives secure message stowing away while keeping up subtlety quality and high implanting limit. Last spread pictures keeps up PSNR estimation of over 50. Inserting limit is around multiple times higher in contrast with comparative calculation which uses Gray Level Co-event Matrices (GLCM) highlight to recognize complex districts of pictures for information covering up.
Keywords: Versatile Steganography, Unpredictability Examination, Shading Surface Element, CTF, GLCM Surface, DCT.
Scope of the Article: Adaptive Systems