Automatic palette identification of colored graphics

Vinciane Lacroix

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The median-shift, a new clustering algorithm, is proposed to automatically identify the palette of colored graphics, a pre-requisite for graphics vectorization. The median-shift is an iterative process which shifts each data point to the "median" point of its neighborhood defined thanks to a distance measure and a maximum radius, the only parameter of the method. The process is viewed as a graph transformation which converges to a set of clusters made of one or several connected vertices. As the palette identification depends on color perception, the clustering is performed in the L*a*b* feature space. As pixels located on edges are made of mixed colors not expected to be part of the palette, they are removed from the initial data set by an automatic pre-processing. Results are shown on scanned maps and on the Macbeth color chart and compared to well established methods.

Original languageEnglish
Title of host publicationGraphics Recognition
Subtitle of host publicationAchievements, Challenges, and Evolution - 8th International Workshop, GREC 2009, Selected Papers
Pages61-68
Number of pages8
DOIs
Publication statusPublished - 2010
Event8th IAPR Workshop on Graphics Recognition, GREC 2009 - La Rochelle, France
Duration: 22 Jul 200923 Jul 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6020 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th IAPR Workshop on Graphics Recognition, GREC 2009
Country/TerritoryFrance
CityLa Rochelle
Period22/07/0923/07/09

Keywords

  • clustering
  • mean-shift
  • palette extraction

Fingerprint

Dive into the research topics of 'Automatic palette identification of colored graphics'. Together they form a unique fingerprint.

Cite this