Research In Mathematical Features Of Digital Image Forensics

The image forensics based on signature and technology based on watermarking are together called active forensics, which was the research focus of digital image forensics, and then the passive forensics technology emerge. Passive forensics technology don’t need embedded information before forensics, but need to find changes that caused by tampering, and trying to quantify the degree of changes with math theory, and then make a judgment whether the image exists tampering. Passive image forensics technology is the focus of image forensics area now.An introduction of the history of image forensics, a detailed analysis of forensics significance in real life and summary of research results of home and abroad are given, and our research work are based on these. With the camera calibration technique, we analyze text image forensics model and study the mathematical characteristics which changes caused by tampering, and use such characteristics as the identification to detect Chinese characters’authenticity. Study of the difference between the image obtained by camera and image editing software, we use of mathematical theory to quantify the difference in value, with support vector machine to get classification model. We achieve detecting the authenticity image identification, and expansion of existing forensic technology scope. The research results include the following:Based on camera calibration theory, using characteristics of Chinese characters with flat, strokes interchange, we introduced Chinese characters model to estimate the projection rule of Chinese characters in digital image. Since there is size of proportional between Chinese characters model and the actual Chinese character, and is constant difference between estimated projection rules and the homography. The estimation method to break the limitations that the traditional camera calibration needs to known a certain size of calibration object. Introduced the idea of Chinese characters reconstructed, and to extract a certain number of strokes in the intersection represent Chinese characters, compare reconstructed Chinese characters with the corresponding character model, we use the differences mean of more than one intersection to describe the degree of projection deviation. Projection deviation value of multiple character images that known authenticity is estimated. With the method of depicting the projection deviation value curve to determine threshold, when the projection deviation is greater than the threshold, we judge that image was tampered.The limitations of text image forensics technology in the actual operation are that the text surface is flat, and has difficulties to detect tampering part text. In order to break these limitations, we study the differences between digital camera photo and image obtained by editing software, we use kurtosis, differential and so on to quantify the degree of differences. Using the idea of splitting the text to solve the problem that the existing forensics technology can’t detect text part tampering, suspected from the image divided stroke region, we extract characteristics of strokes of the edge point. On the basis of a large number pictures that known authenticity, we use support vector machine to training classification model, and then to achieve authenticity of text image the identification.