Image Splicing detection based on image quality and analysis of variance
In this paper an image splicing detection scheme is proposed. The scheme is based on image quality and analysis of variance. Four kinds of noise used to simulated the image quality changes which caused by tampering of images, and analysis of variance is used to selected the image quality measures which are more sensitive to image blind splicing detection. Combined with the characteristic function moments of threelevel wavelet sub-bands and the further decomposition coefficients of the first scale diagonal sub-band, we extracted all features from given image and its predicted error image. SVM is adopted as the classifier to train and test the given images. The simulation results show the proposed scheme has good performance in the average detection accuracy increased by about 1.5％ ~ 15％ than the existed methods.
image forgery detection analysis of variance(ANOVA) image quality measures (lQMs) moments of characteristic function
ZHOU Zhi-ping ZHANG Xiao-xiang
Department of communication and control engineering Jiangnan university Wuxi, China
国际会议
上海
英文
242-246
2010-06-22（万方平台首次上网日期，不代表论文的发表时间）