Abstract: As one of the most popular image scaling technologies in recent years,seam carving is often used for malicious tampering.We find that there are two shortcomings in the current research work of seam carving tamper detection.First,the detection methods are basically aimed at tampered JPEG image.For tampered TIFF image,the current detection methods have low accuracy.Second,when the ratio of seam carving tampering is small,the classification accuracy is relatively low.In order to solve these problems,this paper proposes a seam car-ving tamper detection method based on discrete Tchebichef transform.The tamper detection method is no longer limited to the image format,can effectively detect the tampered images of various formats,and maintain a high classification accuracy.In addition,when the tampering ratio is small,this method will not fail,and has a high classification accuracy.The method in this paper users the distribution characteristics of the coefficients in the coefficient matrix after the discrete Tchebichef transform to extract features to detect seam carved images.Moreover,this method is suitable for all kinds of image formats,and maintains a high classification accuracy under the condition of small tampering ratio.The proposed method makes use of the distribution characteristics of the coefficients in the coefficient matrix after discrete Tchebichef transform.After image segmentation and discrete Tchebichef transform,the value of the coefficient in the upper left corner of each block is very large,and the value in other positions is very small.The trace of seam carving is extracted and the tamper detection of seam carving is realized.Based on the characteristics of coefficient distribution in discrete Tchebichef transform coefficient matrix,the classification accuracy will not be affected by compression quality factor and will not change with the change of compression quality factor.The steps of this detection method are as follows.Firstly,the images are divided into 8×8 non-overlapping blocks,and then each block of the image is transformed by discrete Tchebichef transform to get the transformed coefficient matrix.Due to the characteristics of discrete Tchebichef transform,the coefficients of the upper left corner of each 8×8 block of the coefficient matrix are very large,and the coefficients of other positions are very small,so the differences between coefficients are calculated in each block of the coefficient matrix,and the histogram of the differences between coefficients is obtained.Finally,the statistical matrix is obtained from the histogram of the differences between the coefficients,and the features are extracted from the statistical matrix.The extracted features are sent to SVM for training,and a classification model is obtained.In this paper,a seam car-ving tamper detection method based on discrete Tchebichef transform is proposed to classify original images and tampered images.The experimental results show that this method can achieve high classification accuracy.The detection method based on discrete Tchebichef transform proposed in this paper can achieve high classification accuracy both in JPEG tampered image and TIFF tampered image,and also can achieve high detection accuracy for small-scale tampering.

Key words: Discrete Tchebichef transform, Image forensics, Image resizing, Seam carving, Tamper detection