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Authors: Xiaoliang Xiong ; Jie Feng and Bingfeng Zhou

Affiliation: Peking University, China

ISBN: 978-989-758-175-5

Keyword(s): Vectorization, Real-time Rendering, GPU Acceleration.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; High-Performance Computing and Parallel Rendering ; Interactive Environments ; Real-Time Graphics ; Real-Time Rendering ; Rendering

Abstract: In this paper, we present a novel algorithm to convert a raster image into its vector form. Different from the state-of-art methods, we explore the potential parallelism that exists in the problem and propose an algorithm suitable to be accelerated by the graphics hardware. In our algorithm, the vectorization task is decomposed into four steps: detecting the boundary pixels, pre-computing the connectivity relationship of detected pixels, organizing detected pixels into boundary loops and vectorizing each loop into line segments. The boundary detection and connectivity pre-computing are parallelized owing to the independence between scanlines. After a sequential boundary pixels organizing, all loops are vectorized concurrently. With a GPU implementation, the vectorization can be accomplished in real-time. Then, the image can be represented by the vectorized contour. This real-time vectorization algorithm can be used on images with multiple silhouettes and multi-view videos. We demonstrate the efficiency of our algorithm with several applications including cartoon and document vectorization. (More)

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Paper citation in several formats:
Xiong, X.; Feng, Jie and Zhou, B. (2016). Real-time Image Vectorization on GPU.In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 143-150. DOI: 10.5220/0005668901410148

@conference{grapp16,
author={Xiaoliang Xiong. and Feng, Jie and Bingfeng Zhou.},
title={Real-time Image Vectorization on GPU},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2016)},
year={2016},
pages={143-150},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005668901410148},
isbn={978-989-758-175-5},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2016)
TI - Real-time Image Vectorization on GPU
SN - 978-989-758-175-5
AU - Xiong, X.
AU - Feng, Jie
AU - Zhou, B.
PY - 2016
SP - 143
EP - 150
DO - 10.5220/0005668901410148

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