Abstract: Digital image passive blind forensics aim to distinguish the integrity and authenticity of digital images．After the image is tampered, in order to eliminate the visual edge distortion caused by splicing during the process of forgery, some post-processing operations are usually utilized to eliminate the tampering traces. For example, manual blurring is one of the common approaches. Based on this condition, a method which can detect manual blurring from the tampered image is proposed. Firstly, the features of the image edges are analyzed by using nonsubsampled contourlet, by which the image edges can be classified. Then the authors can distinguish whether the edge is blurred by the differences between the normal edge and the blurred edge. Finally, local definition which is defined to indicate the differences between the manual blurring and out of focus, can be used to locate the manual blurred traces. Experimental results show that this method can detect possible manual blurring in the given tested images and locate the tampered boundary with a relative high accurate rate. The more serious the image blurred edge is, the better performance the method has. Compared with the other blurring detection approaches, the method presented has the capability of pixel-location.