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With advances in image display technology, recapturing good-quality images from the high-fidelity artificial scenery on a LCD screen becomes possible. Such image recapturing posts a security threat, which allows the forgery images to bypass the current forensic systems. In this paper, we first recapture some good-quality photos on different LCD screens by properly setting up the recapturing environment and tuning the controllable settings. In a perceptional study, we find that such finely recaptured images can hardly be identified by human eyes. To prevent the image recapturing attack, we propose a set of statistical features, which capture the common anomalies introduced in the camera recapturing process on LCD screens. With a probabilistic support vector machine classifier, comparison results show that our proposed features work very well, which outperform the conventional image forensic features in identification of the finely recaptured images.