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

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9596)

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.

Keywords

Computational intelligence Non-photorealistic rendering Brush stroke extraction Painterly rendering Flock simulation Autonomous agents Swarm intelligence 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.University of CanterburyChristchurchNew Zealand

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