A Spatial Domain Steganography for Grayscale Documents Using Pattern Recognition Techniques

Steganography is an effective way to hide a secret message into a document image with the objective of providing authenticity of transmitted documents. Steganography has been widely used for natural images but few researches have been carried out to apply this strategy on document images. In this study, we proposed a novel data hiding scheme that enables to embed a secret information with moderate length by taking advantages of pattern recognition techniques. Firstly, the potential feature points used for constructing embedding regions are identified by using the Speed Up Robust Features (SURF) detector. Secondly, Local Binary Pattern (LBP) is utilized to figure out embedding patterns inside each embedding region, Local Ternary Pattern (LTP) are then effectively exploited to locate the stable embedding positions inside embedding patterns in which the secret bits are embedded in. Finally, to make the scheme being robust against document rotation caused by distortion of printing and scanning process, Hough transform is applied to compute the rotation angle for restoring rotated document to original direction. Besides, repetition code and other improved methods are implemented to possibly enhance the accuracy of extracted secret data. The proposed steganography scheme in spatial domain is capable of detecting embedded data without any references and resisting to common image processing distortion.