Abstract
Even though digitally filtered images are taking over the Internet for their aesthetic appeal, general people often feel betrayed if they are dealt with filtered images. Our study, comprising a series of structured surveys over images filtered using Instagram filters, reveals that different people perceive the filtered images differently. However, people have a common need for an automated tool to help them distinguish between original and filtered images. Accordingly, we develop an automated tool named ‘InnerEye’, which is capable of identifying how far an image is filtered or not. InnerEye utilizes a novel analytical design of a Neural Network Model that learns from a diverse set of images filtered using Instagram filters. Rigorous objective and subjective evaluations confirm the efficacy of InnerEye in identifying the extent of filtering in the images.
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The work was conducted at and supported by the Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh.
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Rakib, G.A. et al. (2023). InnerEye: A Tale on Images Filtered Using Instagram Filters - How Do We Interact with them and How Can We Automatically Identify the Extent of Filtering?. In: Longfei, S., Bodhi, P. (eds) Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 492. Springer, Cham. https://doi.org/10.1007/978-3-031-34776-4_26
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