Non-Photorealistic Rendering Using CUDA-Based Image Segmentation


KIPS Transactions on Software and Data Engineering, Vol. 4, No. 11, pp. 529-536, Nov. 2015
10.3745/KTSDE.2015.4.11.529,   PDF Download:

Abstract

When rendering both three-dimensional objects and photo images together, the non-photorealistic rendering results are in visual discord since the two contents have their own independent color distributions. This paper proposes a non-photorealistic rendering technique which renders both three-dimensional objects and photo images such as cartoons and sketches. The proposed technique computes the color distribution property of the photo images and reduces the number of colors of both photo images and 3D objects. NPR is performed based on the reduced colormaps and edge features. To enhance the natural scene presentation, the image region segmentation process is preferred when extracting and applying colormaps. However, the image segmentation technique needs a lot of computational operations. It takes a long time for non-photorealistic rendering for large size frames. To speed up the time-consuming segmentation procedure, we use GPGPU for the parallel computing using the GPU. As a result, we significantly improve the execution speed of the algorithm.


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Cite this article
[IEEE Style]
H. C. Yoon and J. S. Park, "Non-Photorealistic Rendering Using CUDA-Based Image Segmentation," KIPS Transactions on Software and Data Engineering, vol. 4, no. 11, pp. 529-536, 2015. DOI: 10.3745/KTSDE.2015.4.11.529.

[ACM Style]
Hyun Cheol Yoon and Jong Seung Park. 2015. Non-Photorealistic Rendering Using CUDA-Based Image Segmentation. KIPS Transactions on Software and Data Engineering, 4, 11, (2015), 529-536. DOI: 10.3745/KTSDE.2015.4.11.529.