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In today's age of internet and social media, one can find an enormous volumeof forged images on-line. These images have been used in the past to conveyfalsified information and achieve harmful intentions. The spread and the effectof the social media only makes this problem more severe. While creating forgedimages has become easier due to software advancements, there is no automatedalgorithm which can reliably detect forgery.  Image forgery detection can be seen as a subset of image understandingproblem. Human performance is still the gold-standard for these type ofproblems when compared to existing state-of-art automated algorithms. Weconduct a subjective evaluation test with the aid of eye-tracker to investigateinto human factors associated with this problem. We compare the performance ofan automated algorithm and humans for forgery detection problem. We alsodevelop an algorithm which uses the data from the evaluation test to predictthe difficulty-level of an image (the difficulty-level of an image here denoteshow difficult it is for humans to detect forgery in an image. Terms such as"Easy/difficult image" will be used in the same context). The experimentalresults presented in this paper should facilitate development of betteralgorithms in the future.

Investigating Human Factors in Image Forgery Detection