IMAGE-BASED PAINTERLY RENDERING BY EVOLUTIONARY ALGORITHM

Uday K. Chakraborty (), Hyung W. Kang () and Paul P. Wang
Additional contact information
Uday K. Chakraborty: Department of Mathematics and Computer Science, University of Missouri - St. Louis, One University Blvd., St. Louis, MO 63121, USA
Hyung W. Kang: Department of Mathematics and Computer Science, University of Missouri - St. Louis, One University Blvd., St. Louis, MO 63121, USA
Paul P. Wang: Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA

New Mathematics and Natural Computation (NMNC), 2007, vol. 03, issue 02, 239-257

Abstract: This paper presents an effective method based on genetic algorithm for optimizing the rendering quality in image-based painterly rendering. Based on a multi-level evolutionary approach, the proposed method produces, for a variety of input images, results that are better in a statistically significant way than previous methods.

Keywords: Non-photorealistic rendering; painterly rendering; computer graphics; optimization; evolutionary algorithm (search for similar items in EconPapers)
Date: 2007
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S1793005707000732
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:nmncxx:v:03:y:2007:i:02:n:s1793005707000732

Ordering information: This journal article can be ordered from

DOI: 10.1142/S1793005707000732

Access Statistics for this article

New Mathematics and Natural Computation (NMNC) is currently edited by Paul P Wang

More articles in New Mathematics and Natural Computation (NMNC) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().