Iterative Brush Path Extraction Algorithm for Aiding Flock Brush Simulation of Stroke-Based Painterly Rendering

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Tieta Putri, Ramakrishnan Mukundan: Iterative Brush Path Extraction Algorithm for Aiding Flock Brush Simulation of Stroke-Based Painterly Rendering. In: EvoMUSART 2016, 152-162.

DOI

http://dx.doi.org/10.1007/978-3-319-31008-4_11

Abstract

Painterly algorithms form an important part of non-photorealistic rendering (NPR) techniques where the primary aim is to incorporate expressive and stylistic qualities in the output. Extraction, representation and analysis of brush stroke parameters are essential for mapping artistic styles in stroke based rendering (SBR) applications. In this paper, we present a novel iterative method for extracting brush stroke regions and paths for aiding a particle swarm based SBR process. The algorithm and its implementation aspects are discussed in detail. Experimental results are presented showing the painterly rendering of input images and the extracted brush paths.

Extended Abstract

Bibtex

@incollection{
year={2016},
isbn={978-3-319-31007-7},
booktitle={Evolutionary and Biologically Inspired Music, Sound, Art and Design},
volume={9596},
series={Lecture Notes in Computer Science},
editor={Johnson, Colin and Ciesielski, Vic and Correia, João and Machado, Penousal},
doi={http://dx.doi.org/10.1007/978-3-319-16498-4_11},
title={Iterative Brush Path Extraction Algorithm for Aiding Flock Brush Simulation of Stroke-Based Painterly Rendering},
url={http://link.springer.com/chapter/10.1007/978-3-319-31008-4_11  http://de.evo-art.org/index.php?title=Iterative_Brush_Path_Extraction_Algorithm_for_Aiding_Flock_Brush_Simulation_of_Stroke-Based_Painterly_Rendering},
publisher={Springer International Publishing},
keywords={Computational intelligence, Non-photorealistic rendering, Brush stroke extraction, Painterly rendering, Flock simulation, Autonomous agents, Swarm intelligence},
author={Putri, Tieta and Mukundan, Ramakrishnan},
pages={152-162},
language={English}
}

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