Optimization of paintbrush rendering of images by dynamic MCMC methods

Tamás Szirányi, Zoltán Tóth

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

We have developed a new stochastic image rendering method for the compression, description and segmentation of images. This paintbrush-like image transformation is based on a random searching to insert brush-strokes into a generated image at decreasing scale of brush-sizes, without predefined models or interaction. We introduced a sequential multiscale image decomposition method, based on simulated rectangular-shaped paintbrush strokes. The resulting images look like good-quality paintings with well-defined contours, at an acceptable distortion compared to the original image. The image can be described with the parameters of the consecutive paintbrush strokes, resulting in a parameter-series that can be used for compression. The painting process can be applied for image representation, segmentation and contour detection. Our original method is based on stochastic exhaustive searching which takes a long time of convergence. In this paper we propose a modified algorithm of speed up of about 2x where the faster convergence is supported by a dynamic Metropolis Hastings rule.

Original languageEnglish
Title of host publicationEnergy Minimization Methods in Computer Vision and Pattern Recognition - 3rd International Workshop, EMMCVPR 2001, Proceedings
EditorsAnil K. Jain, Mario Figueiredo, Josiane Zerubia
PublisherSpringer Verlag
Pages201-215
Number of pages15
ISBN (Print)3540425233, 9783540425236
DOIs
Publication statusPublished - Jan 1 2001
Event3rd International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2001 - Sophia Antipolis, France
Duration: Sep 3 2001Sep 5 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2134
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2001
CountryFrance
CitySophia Antipolis
Period9/3/019/5/01

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Szirányi, T., & Tóth, Z. (2001). Optimization of paintbrush rendering of images by dynamic MCMC methods. In A. K. Jain, M. Figueiredo, & J. Zerubia (Eds.), Energy Minimization Methods in Computer Vision and Pattern Recognition - 3rd International Workshop, EMMCVPR 2001, Proceedings (pp. 201-215). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2134). Springer Verlag. https://doi.org/10.1007/3-540-44745-8_14