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Methods to Distinguish Photorealistic Computer Generated Images from Photographic Images: A Review

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Advances in Computing and Data Sciences (ICACDS 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1045))

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Abstract

Uses of digital images have increased multifold in last few years in various important fields such as virtual reality, gaming, social media, magazine, news papers, medical, legal issues, law, academics etc. At the same time, image editing and rendering tools have also evolved significantly. With the help of computers and such advanced image rendering tools it is possible to create photorealistic computer graphics images effortlessly. It is very difficult to discriminate such photorealistic computer graphics images from actual photographic images taken from digital cameras by human visual system. If computer generated images are used with malicious intentions it creates negative impact on the society. Therefore, several methods have been proposed in last few years to distinguish computer generated images from photographic images. This paper presents a comprehensive review of the existing methods. A classification of all existing methods is also provided based on the use of feature extraction techniques and classifier used. Accordingly, all the existing methods are grouped into four categories: statistical feature based, acquisition process based, visual feature based, and hybrid feature based methods. This paper also reviews publically available related image datasets and suggests the future directions.

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Authors and Affiliations

  1. Jaypee University of Engineering and Technology, Raghogarh, Guna, MP, India

    Kunj Bihari Meena & Vipin Tyagi

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  1. Kunj Bihari Meena
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  2. Vipin Tyagi
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Correspondence to Vipin Tyagi .

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Editors and Affiliations

  1. University of KwaZulu-Natal, Durban, South Africa

    Mayank Singh

  2. Computer Science and Engineering, Jaypee Institute of Information Technology, Waknaghat, Himachal Pradesh, India

    P.K. Gupta

  3. Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

    Vipin Tyagi

  4. ÚTIA AV ČR, Institute of Information Theory and Automation, Prague 8, Praha, Czech Republic

    Jan Flusser

  5. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada

    Tuncer Ören

  6. CSE Department, Inderprastha Engineering College, Ghaziabad, Uttar Pradesh, India

    Rekha Kashyap

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Meena, K.B., Tyagi, V. (2019). Methods to Distinguish Photorealistic Computer Generated Images from Photographic Images: A Review. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T., Kashyap, R. (eds) Advances in Computing and Data Sciences. ICACDS 2019. Communications in Computer and Information Science, vol 1045. Springer, Singapore. https://doi.org/10.1007/978-981-13-9939-8_7

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