NDLI: Investigating Human Factors in Image Forgery Detection

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Investigating Human Factors in Image Forgery Detection

Investigating Human Factors in Image Forgery Detection

Content Provider	ACM Digital Library
Author	Li, Baoxin Chandakkar, Parag Shridhar
Abstract	In today's age of internet and social media, one can find an enormous volume of forged images on-line. These images have been used in the past to convey falsified information and achieve harmful intentions. The spread and the effect of the social media only makes this problem more severe. While creating forged images has become easier due to software advancements, there is no automated algorithm which can reliably detect forgery. Image forgery detection can be seen as a subset of image understanding problem. Human performance is still the gold-standard for these type of problems when compared to existing state-of-art automated algorithms. We conduct a subjective evaluation test with the aid of eye-tracker to investigate into human factors associated with this problem. We compare the performance of an automated algorithm and humans for forgery detection problem. We also develop an algorithm which uses the data from the evaluation test to predict the difficulty-level of an image. The experimental results presented in this paper should facilitate development of better algorithms in the future.
Starting Page	41
Ending Page	44
Page Count	4
File Format	PDF
ISBN	9781450331203
DOI	10.1145/2660505.2660510
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-11-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Eye-tracking Subjective evaluation Image forgery
Content Type	Text
Resource Type	Article

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