On LSB Data Hiding in High-Definition Images Using Morphological Operations

The aim of steganography is to conceal the presence of communication by way of hiding secret data in perceptually irrelevant parts of a cover object. In this paper, we propose a method for hiding secret images in edge regions of high-definition (HD) images because the human visual system is less sensitive to intensity changes in these regions. In particular, least significant bit substitution is used to embed a secret image in the edge regions of a HD cover image. The edge regions are obtained using a Canny edge detector followed by morphological operations which are used to control the hiding capacity. A performance assessment of the proposed method reveals the trade-off between capacity, detectability, and perceptibility of the hidden data.

[1]  Shuliang Sun,et al.  A novel edge based image steganography with 2k correction and Huffman encoding , 2016, Inf. Process. Lett..

[2]  Andriana Olmos,et al.  A biologically inspired algorithm for the recovery of shading and reflectance images , 2004 .

[3]  Sylvain Paris,et al.  Learning photographic global tonal adjustment with a database of input / output image pairs , 2011, CVPR 2011.

[4]  Martin J. Tovée.  An introduction to the visual system [2nd ed.] , 2008 .

[5]  Alan C. Bovik,et al.  Image information and visual quality , 2006, IEEE Trans. Image Process..

[6]  Umesh Ghanekar,et al.  Image steganography based on Canny edge detection, dilation operator and hybrid coding , 2018, J. Inf. Secur. Appl..

[7]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[8]  Chin-Chen Chang,et al.  High payload steganography mechanism using hybrid edge detector , 2010, Expert Syst. Appl..

[9]  Jiwu Huang,et al.  Edge Adaptive Image Steganography Based on LSB Matching Revisited , 2010, IEEE Transactions on Information Forensics and Security.

[10]  Markus G. Kuhn,et al.  Information hiding-a survey , 1999, Proc. IEEE.

[11]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Jessica J. Fridrich,et al.  Detecting LSB Steganography in Color and Gray-Scale Images , 2001, IEEE Multim..

[13]  J. K. Mandal,et al.  High payload image steganography based on Laplacian of Gaussian (LoG) edge detector , 2018, Multimedia Tools and Applications.

[14]  J. Mielikainen.  LSB matching revisited , 2006, IEEE Signal Processing Letters.

[15]  Javaid A. Sheikh,et al.  Information hiding in edges: A high capacity information hiding technique using hybrid edge detection , 2016, Multimedia Tools and Applications.

[16]  Arup Kumar Pal,et al.  Design of an Edge Detection Based Image Steganography with High Embedding Capacity , 2013, QSHINE.

[17]  H. Dadgostar,et al.  Image steganography based on interval-valued intuitionistic fuzzy edge detection and modified LSB , 2016, J. Inf. Secur. Appl..

[18]  Paul Wintz,et al.  Digital image processing (2nd ed.) , 1987 .

[19]  Anand Singh Jalal,et al.  LSB based non blind predictive edge adaptive image steganography , 2017, Multimedia Tools and Applications.

[20]  Xinhua Zhuang,et al.  Image Analysis Using Mathematical Morphology , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  Hsien-Wen Tseng,et al.  High-payload block-based data hiding scheme using hybrid edge detector with minimal distortion , 2014, IET Image Process..

[22]  Chin-Chen Chang,et al.  A high payload steganographic algorithm based on edge detection , 2017, Displays.

[23]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Kathiresh Mayilsamy,et al.  An integrated approach for data security in vehicle diagnostics over internet protocol and software update over the air , 2018, Comput. Electr. Eng..

[25]  Sahib Khan,et al.  Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region , 2018 .