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A comprehensive survey on non-photorealistic rendering and benchmark developments for image abstraction and stylization

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Abstract

This survey presents a comprehensive study on non-photorealistic rendering (NPR). NPR technique renders 2D input image into abstracted and artistic stylized images. NPR mainly dwells on image processing, computer vision, and visualizing the graphics processing techniques. The survey highlights the evolution of IA–AR system and the subsequent classification of NPR techniques. The survey also has cognized the various works done on stroke-based rendering, color image analogy, region-based rendering, image filtering abstraction, and stylization. The inference drawn from the survey is the computer system using a stylus to fully automatic structure-preserving image abstraction and stylization got evolved from a traditional method of human interaction. From the survey carried out on the most significant papers from 1963 to 2017, we felt the need for setting up of benchmark guidelines, the data set with varies subjective matters, and quality assessment techniques with various statistical essences. From the survey information pertaining to benchmark image characteristics, properties and their constraints with the contextual feature in an image have been identified. Finally, survey work listed out the NPR application in various fields of image processing and highlighted empirical challenges and hampers in NPR domain. This survey work has empowered us to proceed in the right direction and enthusiasm to bring forth the problem statement and carry out research work.

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Acknowledgements

During our work involving setting up of benchmark data set, many noteworthy images were scrutinized. We the authors offer our heartfelt thanks for the following authors and resource persons for their courtesy in publishing the images pertaining to their work. (1) Dr Jan Eric Kypriandis and associates. (2) Dr Henry Kang and associates. (3) Ar.Yeshaswini Rondamath, Asst.Professor, BMSSA, Bangalore. (4) Prof. Vishwas CGM, Asst. Professor. JNNCE, Shivamogga. (5) Dr Nirmala Shivananda. Prof and Head, Dept. of CSE. JNNCE Shivamogga. Our thanks are due to Dr David Mould for the valuable suggestion in assessing the image property.

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  1. Department of Information Science and Engineering, Jawaharlal Nehru National College of Engineering, Shivamogga, India

    M. P. Pavan Kumar

  2. Department of Information Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, India

    B. Poornima

  3. Department of Studies in Computer Science, University of Mysore, Mysuru, India

    H. S. Nagendraswamy

  4. Department of Mechanical Engineering, Jawaharlal Nehru National College of Engineering, Shivamogga, India

    C. Manjunath

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Kumar, M.P.P., Poornima, B., Nagendraswamy, H.S. et al. A comprehensive survey on non-photorealistic rendering and benchmark developments for image abstraction and stylization. Iran J Comput Sci 2, 131–165 (2019). https://doi.org/10.1007/s42044-019-00034-1

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