A steganographic method for images by pixel-value differencing
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Secret image sharing with steganography and authentication
Journal of Systems and Software
Reliable detection of LSB steganography in color and grayscale images
MM&Sec '01 Proceedings of the 2001 workshop on Multimedia and security: new challenges
A high quality steganographic method with pixel-value differencing and modulus function
Journal of Systems and Software
Adaptive Data Hiding in Edge Areas of Images With Spatial LSB Domain Systems
IEEE Transactions on Information Forensics and Security
IEEE Transactions on Information Forensics and Security
Pattern-Based Data Hiding for Binary Image Authentication by Connectivity-Preserving
IEEE Transactions on Multimedia
Secret image sharing with authentication-chaining and dynamic embedding
Journal of Systems and Software
Journal of Systems and Software
A compression-based text steganography method
Journal of Systems and Software
Human visual system based data embedding method using quadtree partitioning
Image Communication
Adaptive image data hiding in edges using patched reference table and pair-wise embedding technique
Information Sciences: an International Journal
Color local complexity estimation based steganographic (CLCES) method
Expert Systems with Applications: An International Journal
A novel approach to digital watermarking, exploiting colour spaces
Signal Processing
High payload data-hiding in audio signals based on a modified OFDM approach
Expert Systems with Applications: An International Journal
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This paper presents a novel adaptive steganographic scheme that is capable of both preventing visual degradation and providing a large embedding capacity. The embedding capacity of each pixel is dynamically determined by the local complexity of the cover image, allowing us to maintain good visual quality as well as embedding a large amount of secret messages. We classify pixels into three levels based on the variance of the local complexity of the cover image. When determining which level of local complexity a pixel should belong to, we take human vision sensitivity into consideration. This ensures that the visual artifacts appeared in the stego image are imperceptible, and the difference between the original and stego image is indistinguishable by the human visual system. The pixel classification assures that the embedding capacity offered by a cover image is bounded by the embedding capacity imposed on three levels that are distinguished by two boundary thresholds values. This allows us to derive a combination ratio of the maximal embedding capacity encountered with at each level. Consequently, our scheme is capable of determining two threshold values according to the desired demand of the embedding capacity requested by the user. Experimental results demonstrated that our adaptive steganographic algorithm produces insignificant visual distortion due to the hidden message. It provides high embedding capacity superior to that offered by a number of existing schemes. Our algorithm can resist the RS steganalysis attack, and it is statistically invisible for the attack of histogram comparison. The proposed scheme is simple, efficient and feasible for adaptive steganographic applications.