Because of the rapidly increasing use of digital composite images, recent studies have identified digital forgery and filtering regions. This research has shown that interpolation, which is used to edit digital images, is an effective way to analyze digital images for composite regions. Interpolation is widely used to adjust the size of the image of a composite target, making the composite image seem natural by rotating or deforming. As a result, many algorithms have been developed to identify composite regions by detecting a trace of interpolation. However, many limitations have been found in detection maps developed to identify composite regions. In this study, we analyze the pixel patterns of noninterpolation and interpolation regions. We propose a detection map algorithm to separate the two regions. To identify composite regions, we have developed an improved algorithm using minimum filer, Laplacian operation and maximum filters. Finally, filtering regions that used the interpolation operation are analyzed using the proposed algorithm.

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This study designs a method of identifying the camera model used to take videos that are distributed through mobile phones and determines the original version of the mobile phone video for use as legal evidence. For this analysis, an experiment was conducted to find the unique characteristics of each mobile phone. The videos recorded by mobile phones were analyzed to establish the delay time of sound signals, and the differences between the delay times of sound signals for different mobile phones were traced by classifying their characteristics. Furthermore, the sound input signals for mobile phone videos used as legal evidence were analyzed to ascertain whether they have the unique characteristics of the original version. The objective of this study was to find a method for validating the use of mobile phone videos as legal evidence using mobile phones through differences in the delay times of sound input signals.