A novel steganalysis of data hiding in binary text images

Through massive experiments we found that for the binary text image embedding algorithm which hiding information by flipping central pixels of the image block, the statistics of run length between cover image and the image after been embedded is different obviously, but which between stego image and the image after test embedding is similar. Based on this law, a novel technique for the steganalysis of binary text image is presented in this paper. In which a test message is embedded in the text image firstly, then the run length statistic difference between text image and the image after embedded is calculated. When the difference exceeds the threshold value, the image is a cover image, otherwise it¿s a stego image. Through the classification experiment, the threshold of several typical characters had identified and the experimental results showed that the detection rate can reach 99.9% by using of the proposed method and the related threshold.